The Entropy Structure of Health and the Information-Energy Consistency Principle: The Ontological Foundation and Regulatory Logic of Proactive Medicine
Yucong Duan
International Standardization Committee of Networked DIKWPfor Artificial Intelligence Evaluation(DIKWP-SC)
World Academy for Artificial Consciousness(WAAC)
World Artificial Consciousness CIC(WAC)
World Conference on Artificial Consciousness(WCAC)
(Email: duanyucong@hotmail.com)
Introduction: The Expansion of the Health Concept and Paradigm Shift
For a long time, "health" has been narrowly equated with the "absence of disease" in many contexts. However, as modern medical concepts continue to evolve, the concept of health has undergone significant expansion and dynamization. As early as 1948, the World Health Organization proposed that health is not just the absence of disease or infirmity, but a multidimensional standard of "a state of complete physical, mental and social well-being" (WHO, 1948). Since then, scholars have further pointed out that rather than viewing health as a static perfect state, it is better to understand it as a dynamic process, namely the adaptability and self-management ability of an individual in the face of physiological, psychological, and social challenges. Huber et al. (2011) based their definition of health as the adaptation and self-management in the face of various challenges on this, and this dynamic concept of health laid the conceptual foundation for proactive medicine: Health is not a static endpoint, but a continuous process of maintaining balance and adaptation.
Proactive medicine goes a step further on this concept, systematically understanding health from the perspective of an open life system. Health is regarded as the product of multi-level coordination between the individual and their environment (including social and natural): a true state of health can only be determined when factors such as physiology, psychology, society, and ecological environment achieve a dynamic balance. This holistic view of health integrates the ideas of the bio-psycho-social medical model, and also expands to include ecological and informational dimensions, interpreting health as an orderly state in an open system, rather than an isolated static indicator. This means that medicine needs to pay attention to the health maintenance of the individual's entire life cycle, as well as the common optimization at the group and environmental levels. Based on this broad vision, proactive medicine elevates the goal of medicine from curing diseases to promoting overall health order.
At its theoretical core, proactive medicine achieves a fundamental shift from the traditional "pathology-centered" paradigm to an "entropy reduction-targeted" paradigm. The traditional biomedical model centers on disease pathology: health is seen as the absence of disease, medical practice focuses on correcting biological abnormalities, and patients passively receive treatment. In contrast, proactive medicine introduces "entropy reduction" as a guiding goal, advocating a proactive, systematic health maintenance paradigm. Entropy was originally a concept in thermodynamics describing the degree of disorder in a system. Physicist Schrödinger, in his famous book, proposed that "life feeds on negative entropy," pointing out that living organisms must continuously ingest orderly energy from the environment to combat their own tendency toward entropy increase; cybernetics pioneer Wiener also emphasized that "information is order," and an increase in information means a reduction in uncertainty, i.e., a reduction in entropy. Drawing on these ideas, proactive medicine regards the essence of health as the process of maintaining and enhancing the orderly degree within the life system, which is essentially the reduction of entropy value or the continuous input of negative entropy. The highest mission of medicine is thus expanded from "eliminating disease" to "maintaining the low-entropy, high-order state of life." This transformation means that medicine no longer only focuses on local lesions, but pays more attention to the overall order: how to use various intervention means to keep the body in a stable and coordinated state at the physiological and informational levels, and resist internal and external disturbances.
The proactive medicine paradigm, which takes entropy reduction as its goal, is embodied in practice as forward-looking health management and preemptive intervention against diseases. The focus of medicine shifts from "disease already formed" to "disease about to arise," and even "preventing disease before it arises." For example, in the prevention and control of chronic diseases, the traditional model often waits until the patient has a clear diagnosis such as hypertension or diabetes before starting treatment; while proactive medicine advocates using means such as wearable devices, remote monitoring, and big data analysis to proactively intervene when physiological indicators just show abnormal signs or risk factors accumulate, avoiding the loss of control of entropy increase that leads to disease outbreaks. This strategy of moving the prevention threshold forward is highly consistent with the "prevention-first" concept of public health. In recent years, the health policies of many countries have also begun to shift from "treating disease" to "promoting health." For example, China's "Healthy China 2030" strategy clearly requires moving the center of gravity of the medical system forward, strengthening the prevention and control of chronic diseases and national healthy lifestyle interventions, and achieving a transformation from being treatment-centered to prevention-centered. This marks that the health management idea guided by entropy reduction has also been recognized at the government level: by proactively intervening to reduce the entropy increase of disease in the whole society, the population is kept in a more orderly state of health.
It needs to be emphasized that "taking entropy reduction as the goal" does not mean ignoring the treatment and research of specific disease causes, but provides a higher-level unifying perspective for medical practice. From the perspective of entropy, the significance of an effective treatment is not only in clearing a certain pathogen or repairing a certain damage, but also in allowing the disordered life system to return to order. For example, the significance of antibiotics curing an infection is to eliminate the chaos caused by the uncontrolled reproduction of microorganisms in the body, so that the physiological internal environment returns to balance; the significance of psychotherapy alleviating depression is to help the brain rebuild an active and orderly information processing and emotional regulation model. Therefore, whether it is biomedical means or psychosocial interventions, their common goal can be interpreted as injecting "negative entropy" into the life system and restoring the coordination of structure and function. This unified perspective helps to integrate the forces of various fields of medicine: clinicians, public health experts, psychological counselors, and even artificial intelligence health algorithm engineers can all understand their own work as a link in participating in "life entropy management." In summary, proactive medicine elevates the mission of medicine to the height of maintaining the order of life, achieving a paradigm revolution from being pathology-centered to entropy-reduction-oriented. This theoretical core provides a brand-new ideological program for us to build an open health system and intelligent intervention paths.
The Negative Entropy Ontology of Health and the Orderliness of Life
"Health" has traditionally been understood as the absence of disease, but from the perspective of proactive medicine, the connotation of health is greatly expanded and dynamized: the health of a life system is essentially a process of maintaining a high degree of internal order and a low entropy value, requiring a continuous supply of orderly energy and information from the environment to combat the natural trend of entropy increase. Physicist Schrödinger pointed out back in the 1940s that "life feeds on negative entropy," meaning that organisms continuously ingest orderly energy and matter from the environment to resist their own fate of tending towards chaos and disintegration; information theory founder Wiener also proposed that "information is order," and an increase in information means a reduction in uncertainty, which is entropy reduction. Drawing on these ideas, proactive medicine regards health as a dynamic balancing process of life continuously reducing entropy and ingesting negative entropy, that is, maintaining internal structural and functional stability and coordination by continuously introducing "order." In other words, the ontological foundation of health can be expressed as a negative entropy ontology: the life-body combats disorder and maintains its own order and vitality through the continuous input of negative entropy flow.
In a healthy state, the functions at all levels of the body operate in coordination, material metabolism and information processing are efficient and orderly, reflecting the high orderliness of the system. For example, a healthy person's physiological indicators such as body temperature and blood pressure are often maintained within a stable range, the brain's cognitive processes are orderly, and emotions are calm and controllable—these are all external manifestations of a low-entropy, high-order state. The key to maintaining this orderly steady state lies in continuously obtaining sufficient "negative entropy" supplies: ample nutrition and energy intake support the body's physiological metabolism and reduce entropy at the material level; while rich sensory learning, social interaction, and other psychological stimuli provide nourishment at the information level, reducing entropy at the cognitive level. Modern scientific research shows that the sources of negative entropy required for health are not limited to material energy such as food and oxygen, but also include information resources such as knowledge and emotional connections. Therefore, to maintain health, individuals need dual nourishment of matter and information.
Conversely, if the supply of negative entropy is insufficient or improperly used, the entropy value of the life system will rise, the internal order will be disrupted, manifested as various imbalances and disorders, that is, an increase in disease risk. Many phenomena in the health field can be explained by entropy increase: when the body cannot effectively obtain or utilize negative entropy, its internal structure and regulatory mechanisms begin to disintegrate, the degree of disorder rises, and various disordered states follow. For example, low immune system function means that the orderly mechanism for clearing pathogens is damaged, resulting in the proliferation of infection in the body (corresponding to entropy increase at the physiological level); severe endocrine and metabolic imbalance will break the body's chemical homeostasis, causing abnormal accumulation of glucose and lipids (entropy increase), manifested as chronic diseases such as diabetes and fatty liver; from the perspective of information cognition, long-term unrelieved psychological stress floods the brain with excessive disordered information, leading to the loss of control of emotional and cognitive regulation (entropy increase), manifested as psychosomatic disorders such as anxiety and depression. It can be said that every disease essentially corresponds to the destruction of the ordered structure at a certain level of life and an abnormal increase in entropy value. What's more serious is that an increase in entropy value also means a decrease in the system's self-stabilizing ability: some minor fluctuations in the past, such as slight discomfort or cell damage, are difficult to be corrected in time in a high-entropy state, and accumulate over time to become irreversible failures. This explains why many chronic diseases have subtle symptoms in the early stages but hide crises—if entropy increase is allowed to develop without intervention, the system's disorder will cross a certain threshold, suddenly triggering a comprehensive collapse of misalignment.
It is precisely because of this that proactive medicine takes inhibiting entropy increase and introducing negative entropy as the basic strategy for maintaining health. This strategy runs through all stages of prevention, diagnosis, and treatment: in prevention, by adopting healthy lifestyles (balanced nutrition, moderate exercise, good sleep, etc.) and regular monitoring, negative entropy is continuously input into the life system (such as obtaining sufficient trace nutrients, maintaining positive psychological activities), to reduce the probability of disease occurrence; in diagnosis, by using big data and artificial intelligence to capture subtle entropy increase signals in vital signs or indicators in time, to achieve early detection of diseases, which is equivalent to correcting deviations in time before entropy gets out of control; in treatment, it is more clearly recognized that any effective therapy is essentially injecting negative entropy into the disordered life system and rebuilding order. Drug treatment corrects biochemical disorders by providing needed molecules, surgical intervention rebuilds the integrity of damaged anatomical structures, and psychotherapy endows new cognitive frameworks and emotional support to sort out chaotic information processing—these methods take different forms, but they all lead to the same goal: pulling the system back from a high-entropy chaotic state to a low-entropy ordered state.
More and more research provides evidence for the effectiveness of entropy reduction in medicine. For example, some scholars have studied the immune recovery process from a thermodynamic perspective, proposing that health status depends on the replenishment of "potential energy" (available orderly energy) in the body and the inhibition of entropy; when factors such as chronic psychological stress or malnutrition lead to an increase in the body's entropy load, this "potential energy" should be supplemented through lifestyle interventions to restore the homeostasis of the immune system. This research result confirms that by enhancing the supply of orderly energy and reducing entropy accumulation, the body's self-stabilizing ability can be enhanced, enabling the immune system to better resist diseases. Another example, some measured data show that the efficiency of entropy discharge often decreases and entropy accumulation intensifies in the state of aging and disease in the human body: as age increases and cardiopulmonary fitness declines, the body's ability to discharge the entropy generated during the metabolic process to the outside world will decrease, leading to the gradual accumulation of entropy in the body; conversely, the stronger the cardiopulmonary function and the better the physical fitness, the less entropy accumulates per unit of time, which means that a good physical fitness state helps the body to deal with the disorder generated by metabolism more effectively. These findings all indicate that consciously maintaining the dynamic balance between negative entropy input and entropy discharge is crucial for delaying aging and preventing diseases.
From the perspective of the entire life process, health can also be understood as an evolutionary curve of the ebb and flow of entropy and negative entropy. In the development stage of childhood, the body grows rapidly and needs to absorb a large amount of negative entropy from the environment (such as nutrients, knowledge, and experience) to establish highly ordered physiological structures and neurocognitive structures; in the adult stage, the body tends to be in a steady state. At this time, it is necessary to balance the intake of negative entropy and the generation of entropy to maintain the dynamic balance of functions; while in old age, due to the gradual decline of body functions, the internal entropy increase rate accelerates. Therefore, it is more necessary to consciously increase the intake of negative entropy (such as strengthening social and mental activities, reasonable nutritional supplements), to delay the aging process caused by the loss of control of entropy increase. We can vividly regard a person's life as a curve of entropy value change: a long and healthy life should strive to extend the time of maintaining a low-entropy steady state, and push the inflection point of sharp entropy increase as far back as possible; and every occurrence of disease will cause a steep peak in the entropy value on the curve. The role of medical intervention is to flatten these peaks as early as possible, so that the entropy value decreases again and returns to a steady state.
Similar entropy management ideas are also applicable to the field of group health and public health. At the macro level, the overall health of a social population also has a problem of "entropy evolution" and regulation: if the lifestyle of the entire society is generally unhealthy (such as the prevalence of high-calorie diets, sedentary behavior), then it is equivalent to the entire group continuously accumulating entropy, manifested as an increase in the incidence of chronic diseases, that is, an increase in macroscopic health disorder. Public health intervention can be seen as a measure to input negative entropy to the population level and reduce entropy increase, thereby restoring the health order at the social level. For example, large-scale health education, environmental governance, and other measures are equivalent to transporting negative entropy to the social "body": tobacco control and salt restriction reduce the input of disordered pathogenic factors, and vaccination improves the orderly degree of group immunity. These all reduce entropy at the macro level and improve the health level. The concept of entropy in information theory thus provides a unified language for connecting micro-individual health and macro-group health: whether it is an individual or a society, the maintenance of health is ultimately the management of entropy. And proactive medicine is precisely based on this "life entropy management," practicing comprehensive intervention from prevention to treatment at different levels, and promoting health through global entropy regulation.
In summary, from the perspective of entropy, health is the process of the life system maintaining a low-entropy, orderly state, while disease and aging mean the out-of-control rise of entropy and the disintegration of order. Proactive medicine is based on the negative entropy ontology, elevates the mission of medicine to the height of maintaining the order of life, and advocates for preventing problems before they occur and coordinating the mind and body through the active regulation of entropy flow, thereby achieving a fundamental shift in the medical paradigm from "disease-centered" to "entropy-centered." This theoretical revolution endows medical practice with a brand-new logic: not to mend the fold after the sheep is lost when the disease appears, but to focus on enhancing the system's self-organization ability and environmental adaptability in daily life, letting life always run on the track of low entropy and high order.
The Coordination Model of Information Field and Energy Field
Proactive medicine, with the help of perspectives from information theory and systems theory, proposes that the health of life can be seen as the synergistic order of the two basic dimensions of the "information field" and the "energy field." Simply put, the Energy Field refers to all energy flow processes that support life activities, including material-level metabolism and energy supply such as thermal energy, chemical energy, and electrical energy; the Information Field refers to all meaningful information content involved inside and outside the life-body, from gene expression regulation, nerve signal transmission to psychological cognition, social interaction, and other "semantic levels." Some scholars have abstractly described life as a negative entropy structure jointly supported by the information field and the energy field. When the two are well coupled, the life system can maintain a high degree of organization and stability; conversely, if information and energy are disconnected or in conflict, the system will appear disordered and move towards disease.
This information-energy field theory breaks the past reductionist concept of equating life merely with machines or chemical reactions, and instead provides a holistic, systems-theory view of health. In a healthy state, the energy field provides sufficient "fuel" and material support for various parts of the body (such as nutrient supply, ATP synthesis, blood oxygen transport), while the information field ensures precise regulation and feedback (such as neuroendocrine coordination, immune recognition and attack, cognitive system decision-making behavior). The two are complementary and mutually reinforcing: without sufficient energy supply, no amount of information commands can be put into practice; similarly, if there is a lack of correct information guidance, excessive energy output may instead cause damage to the body (such as the energy dissipated by overactive immune cells in a cytokine storm, which in turn damages the body). When the information field and the energy field maintain good synergy, the life system operates in an orderly manner, just like an orchestra with all sections cooperating tacitly to play a harmonious movement; but when the two are imbalanced, the system will produce noise and chaos. For example, during a high-fever convulsion, a large amount of energy is dissipated in the form of disordered heat, the energy field is abnormally agitated, but the information field, such as neural regulation, can no longer effectively command the body, resulting in functional disorders such as convulsions and disturbance of consciousness; another example, depressed patients may not have obvious organic lesions physiologically (the energy field is still normal), but their brains are filled with negative and disordered thinking and emotional information (the information field is severely disordered), ultimately leading to dysfunction of behavior and physiological regulation. It can be seen that different types of diseases can be seen as different manifestations of the misalignment of the information field and the energy field.
Based on the above understanding, proactive medicine proposes a new idea of classifying health states according to the coupling status of the information field and the energy field. An intuitive method is to divide the two dimensions of information and energy into "high/low" or "orderly/disordered" states, so as to combine multiple possible health/disease types: for example, "abundant energy-orderly information" represents the ideal healthy state, meaning that the body is energetic and psychological regulation is good, and the mind and body are in a synchronized high-performance state; "low energy-orderly information" describes a weak or sub-health situation, such as insufficient body energy (lack of nutrition or physical fitness) but psychological cognition remains clear and orderly. Such individuals often manifest as physical fatigue but are mentally acceptable; conversely, "abundant energy-disordered information" corresponds to a state of excessive stress or mania. At this time, the body has too much energy but lacks effective cognitive command, like a car engine idling, manifested as excessive physiological activation but disordered behavioral cognition (typical examples include the high metabolic stress caused by hyperthyroidism, or the over-excitation of the sympathetic nervous system accompanied by loss of cognitive control in post-traumatic stress disorder); and "low energy-disordered information" is a pathological state close to collapse, with neither enough energy to maintain basic functions nor orderly information regulation. Typical examples include shock or severe depressive episodes, where patients are often listless and their thinking is confused. This information-energy typing perspective helps to explain many complex clinical phenomena. For example, some patients complain of "being very tired but unable to sleep," which can be understood as the energy field being low but the information field being overactive (the body is exhausted but the brain is still running at high speed, making it difficult to fall asleep); conversely, some patients "are drowsy all day but accompanied by palpitations and night sweats," which may correspond to a situation where the energy field is excessive but the information field regulation is insufficient (the body produces too much energy but lacks appropriate commands to use it, so it can only be vented in a pathological form). The information-energy field model of proactive medicine provides a unified explanatory framework for the above-mentioned seemingly contradictory symptom combinations, enabling clinicians to understand the patient's problems from the perspective of the interaction of energy and information.
More importantly, the information-energy field theory also provides guiding principles for formulating treatment strategies. Proactive medicine emphasizes that when intervening, the two major elements of information and energy should be regulated simultaneously to restore their consistent synergy, in order to truly rebuild health. For the condition of "high energy-disordered information," it is not enough to simply reduce the excess energy (such as using sedatives or antihypertensive drugs to reduce excessive metabolism and blood flow). It should also be supplemented by psychological counseling, behavioral therapy, and other methods to reorganize the information field (such as teaching patients relaxation techniques to reduce the excessive excitement of the central nervous system). Only a two-pronged approach can effectively reduce entropy and alleviate symptoms. Similarly, when facing patients with "low energy-disordered information," if one blindly supplements nutrition and increases energy while ignoring the chaos in their spiritual world, the curative effect will be greatly reduced; it is necessary to, on the one hand, find ways to enhance their physical fitness (such as correcting anemia, improving sleep), and on the other hand, inject "meaning" and "motivation" through psychological support and social care, to help them walk out of their cognitive predicament. Therefore, doctors, in diagnosis and treatment, need to assess the source of the patient's information-energy imbalance: is it insufficient energy supply, or a problem with information regulation, or a deviation in both? Adopt corresponding comprehensive interventions for different types of imbalance. For example, for patients with chronic fatigue syndrome who have almost normal physiological indicators (no obvious abnormality in the energy field) but feel subjectively tired for a long time, it often suggests that the real problem is at the information level: perhaps it is the lack of a sense of life purpose, long-term psychological depression, etc., that leads to the lack of "information energy." At this time, it is necessary to start more from psychological and social support, and input "information-level energy" to the patient, such as psychotherapy, meaning therapy, social interaction, etc. Conversely, some patients with refractory metabolic diseases, although they are very cooperative in lifestyle (a lot of investment at the information level), but due to the low efficiency of the innate metabolic pathways (defects in the energy field), it is difficult to achieve results by relying on lifestyle adjustments alone. Then, drugs or even genetic means are needed to directly intervene in the energy metabolism process to make up for the deficiencies in the energy field.
Through the dual perspectives of the information field and the energy field, proactive medicine can conduct a more comprehensive assessment and intervention on the health status: it pays attention to both the material and energy balance of the "body" and the orderly information processing of the "mind." Any measure that helps to enhance mind-body synchronization and reduce internal contradictions in the system will reduce entropy and improve health; conversely, any new intervention that makes information and energy more disconnected may be counterproductive and needs to be carefully weighed. For example, in the clinical case of controlling hypertension, simply relying on antihypertensive drugs can certainly lower blood pressure readings, but if the patient is chronically nervous due to anxiety about the disease (information field disorder), it may still trigger cardiovascular events; therefore, proactive medicine advocates for combining emotional management and psychological relaxation training (information field intervention) in addition to medication (energy field intervention), to simultaneously reduce physiological stress and psychological stress, and truly reduce disease risk. It is foreseeable that with the development of biosensing technology and digital information technology, we will be able to monitor the state of an individual's information field and energy field more finely, conduct a more accurate "entropy typing" of health, and thus tailor more optimized intervention plans for each person.
The "Information-Energy Consistency" Principle of Mind-Body Systems
The above information-energy coordination view further extends to an important principle, namely the "information-energy consistency" of physiological processes and cognitive processes. The "Free Energy Principle" in modern neuroscience theoretically confirms this: biological systems will spontaneously adjust their internal models (information) to minimize the difference between them and the input from the external environment (energy/sensory stimulation), in other words, to minimize free energy or entropy, thereby maintaining the stability of their own structure. This principle has attracted wide attention in the field of neuroscience and is believed to explain why the brain continuously corrects its own beliefs to match sensory information—by reducing the inconsistency between prediction and reality, the brain is equivalent to reducing information entropy. Similarly, in the context of proactive medicine, the medical knowledge models that doctors and AI rely on can be regarded as the "conceptual field" (information level), and the patient's actual physiological and psychological state as the "semantic field" (energy and semantic level). Only when the prediction of the conceptual field matches the feedback of the semantic field (i.e., information output and energy/sensory input are synchronized) is the entire doctor-patient system in a low-entropy healthy state; conversely, once a deviation occurs, it means that semantics and concepts are inconsistent (information-energy are not isomorphic). At this time, "semantic tension" is generated within the system, which needs to be realigned through further examination or model calibration. This theoretical viewpoint reveals the deep mechanism of how maintaining the synchronization of mind-body information flow and energy flow is essential for preventing entropy from getting out of control and maintaining a healthy steady state.
From the perspective of evolutionary physiology, information-energy consistency has long been embodied in the human stress response. For example, when we encounter a sudden danger, the brain will quickly assess the threat (information processing), and at the same time, the body initiates the "fight or flight" response: the sympathetic nervous system immediately releases adrenaline, increasing heart rate, blood pressure, and muscle energy supply (energy mobilization), putting the body into a state of high alert. At this time, cognitive alertness and high physiological energy output match, and mind-body coordination improves the chances of survival. Conversely, if cognition and energy are disconnected, inefficiency or pathological conditions are likely to occur: anxious patients, in an objectively safe environment, their brains continuously send out excessive threat signals (information overload), while the body has no real energy demand, resulting in unnecessary high-stress responses such as palpitations and sweating, which in the long run will damage physical and mental health; depressed patients are the opposite, their brain thinking falls into a negative and sluggish cycle (information processing is blocked) and body energy mobilization is insufficient (low physiological activation), manifested as slow movement and helplessness. These examples show that health requires cognitive assessment and energy mobilization to maintain an appropriate match: the brain is not overly tense, the body is not overly consumed, and the two are synchronized and rhythmic, so that the body can maintain a low-entropy steady state. This view also echoes the theories of Homeostasis and Allostasis in physiology: homeostasis emphasizes maintaining the stability of internal variables through negative feedback, while allostasis emphasizes the body's active adaptation to changes through predictive regulation to maintain overall homeostasis. A healthy mind and body will carry out appropriate energy allocation and cognitive adjustment according to environmental needs (proactive allostasis), while excessive or wrong predictive regulation (cognitive overload or energy misuse) will destroy the balance, leading to an abnormal increase in entropy levels and health damage.
At the level of daily life, information-energy consistency is embodied in the mind-body synchronization of work and rest patterns and lifestyles. For example, the human sleep-wake circadian rhythm is a typical case: at night, the environmental light is dim, the pineal gland secretes melatonin to gradually quiet down the brain's information processing, and the body's metabolic rate and temperature also decrease accordingly, and the mind and body enter the rest mode together; during the day, the opposite is true, light and external stimuli awaken the brain's cognitive activities, and at the same time, cortisol, etc. rise, prompting the body to increase energy supply. The two jointly bring the body into an awake working state. If a person goes against this natural rhythm for a long time (such as staying up late and reversing day and night), it will break the consistency between the brain's cognitive rhythm and the body's energy metabolism rhythm, which will not only cause declines in cognitive functions such as memory and attention, but also may cause physiological disorders such as endocrine disorders and inflammatory responses—people with chronic insomnia often face both cognitive impairment and metabolic health problems, which is precisely the embodiment of this mind-body entropy disorder. Similarly, in terms of diet and exercise, information-energy synchronization is also crucial: food intake (energy acquisition) should be balanced with the amount of physical activity (energy expenditure), and at the same time, the brain needs to adjust appetite, metabolism, and other signal feedback according to the state of eating and exercise, in order to maintain a balance of nutritional intake and expenditure. If one overeats and lacks exercise, energy intake far exceeds consumption, and the excessive reward signals brought by high-sugar, high-fat diets will interfere with the brain's judgment of satiety (information misalignment), the result is a high-entropy health problem such as excess calories, obesity, and metabolic syndrome. Conversely, by following a moderate diet and adhering to exercise, and guiding reasonable calorie intake and consumption (energy balance) through the brain's accurate perception of hunger and satiety signals (information order), the energy supply and demand and information feedback can be kept consistent, achieving a low-entropy steady-state healthy lifestyle.
In the process of medical intervention, the principle of information-energy consistency reminds us to pay attention to the impact of treatment on the patient's physiology and psychology simultaneously. Take chemotherapy in cancer treatment as an example: it kills tumor cells through toxic drugs, which is a typical strong energy field intervention, but patients often have huge psychological pressure when receiving chemotherapy, filled with negative information such as fear and anxiety. If psychological support (information field intervention) is not provided, the patient's excessive tension may amplify physiological discomfort (such as aggravating nausea, pain), making the originally tolerable treatment difficult to continue. Studies have shown that providing cancer patients with sufficient information support (explaining the treatment process, pain management methods) and psychological counseling can significantly improve their tolerance to chemotherapy and improve their quality of life. This shows that by enhancing the orderliness of the patient's information field (reducing fear, giving faith) to cooperate with high-intensity energy field treatment, the mind and body can be kept relatively consistent, so as to achieve better overall curative effects. Similarly, in the rehabilitation process after surgery, the patient's subjective beliefs and participation enthusiasm (information factors) will affect wound healing and body regeneration ability (energy factors). A patient with a positive attitude who actively cooperates with rehabilitation often recovers faster, because positive information feedback (such as confidence, hope) helps to reduce stress hormone levels and enhance immune function; conversely, negative and depressed emotions will increase the level of stress mediators in the body and inhibit tissue repair. Based on these understandings, proactive medicine regards psycho-social support as an indispensable part of major physical treatment plans, emphasizing that every intervention measure should evaluate its impact on the patient's psychological state, so as to achieve the synchronous improvement of physiological efficacy and psychological comfort as much as possible.
The principle of information-energy consistency also runs through the human-machine collaborative intelligent medical system. When artificial intelligence (AI) intervenes in medical auxiliary decision-making, it is also necessary to ensure that the information output by AI is consistent with the patient's real-life energy status in order to achieve ideal results. If the plan suggested by AI is beyond the patient's affordable range (such as requiring a patient who has been ill for a long time and is weak to perform high-intensity exercise), it is equivalent to a mismatch between information output and actual energy bearing capacity, which is difficult to implement or even counterproductive. Therefore, advanced medical AI should formulate personalized plans based on the patient's real-time physiological data (energy field) and environmental behavior data (information field), and continuously adjust the model parameters by obtaining patient feedback through interaction, so that the AI's "conceptual field" and the patient's "semantic field" remain synchronously calibrated. Such a closed-loop mechanism has already shown initial signs in digital health management: for example, a diabetes management system will automatically adjust medication and lifestyle suggestions based on continuous glucose monitoring data (reflecting energy metabolism) and patient diet and exercise logs (reflecting behavioral information). If the patient does not strictly follow the doctor's advice, the system will detect the inconsistency between information and energy from the abnormal changes in blood glucose data, and promptly update the next intervention strategy. This human-machine closed loop keeps AI's decisions synchronized with the patient's actual state, greatly reducing the incidence of dangerous events such as hypoglycemia or hyperglycemia. It can be seen that in the future medical blueprint built by proactive medicine, the composite system composed of human-machine-environment must also follow the principle of information-energy consistency: AI's wisdom (information output) can only truly promote health when it acts on reality (energy implementation) in a way that fits the patient's physiological capabilities and life context, otherwise the gap between the intelligent algorithm and the disconnected execution will be transformed into system disorder and inefficiency.
In summary, "information-energy consistency," as a core principle of proactive medicine, emphasizes the necessity of high-level coordination of mind and body, knowledge and action, and human and intelligent systems for maintaining a low-entropy healthy state. The physiological energy process and the psychological information process are actually two sides of the same life system: the former provides the material basis, and the latter determines the direction of regulation. The two interact and are inseparable. Therefore, proactive medicine advocates for the integrated consideration of these two factors in prevention and medical practice, to treat both the "body" and guide the "mind," and promote the benign interaction between the two. This principle runs through all levels of proactive medicine: from an individual's daily health management (emphasizing a mind-body balanced lifestyle), to multidisciplinary comprehensive treatment in the clinic (combining physiological treatment with psychological intervention), and then to the humanized design of artificial intelligence-assisted diagnosis and treatment (letting algorithm decisions be close to human real needs), all are guided by ensuring the synergistic consistency of information and energy flow. It can be said that information-energy consistency provides a yardstick for measuring all health intervention measures: any measure that can enhance mind-body synchronization and reduce system internal friction is positive and beneficial; conversely, those practices that split the mind and body or introduce new contradictions need to be treated with great caution. This criterion reminds us that the application of cutting-edge technology must pay attention to the whole person, and medical innovation needs to serve the values and experience of patients. It embodies the "human-centric, mind-body integration" value concept of proactive medicine, and the wisdom of balancing efficiency and ethics and promoting "technology for good" in the new era of emerging technology.
The DIKWP Wisdom Structure and Proactive Regulation Mechanism
In order to apply the above information-energy ontology to intelligent health intervention, proactive medicine has introduced a new generation of cognitive model framework, namely the DIKWP model, to build a proactive intelligent mechanism for human-machine collaboration. DIKWP represents the five levels of Data (D) - Information (I) - Knowledge (K) - Wisdom (W) - Purpose (P). This is an extended model formed by adding a "Purpose" layer to the top of the classic "Data-Information-Knowledge-Wisdom (DIKW)" model. As early as the 1980s, the systems scientist Ackoff proposed the DIKW pyramid to describe the hierarchical relationship of human cognition from raw data to high-level wisdom; while the DIKWP model, by adding the highest "Purpose" dimension, highlights the driving role of goals and values in the cognitive process. In the DIKWP framework, cognition is regarded as a networked interaction structure, rather than a simple linear information processing pipeline: between these five levels, there is not only bottom-up, level-by-level processing, but also top-down feedback regulation, with a total of 5×5=25 different interaction paths possibly formed. In other words, information and energy in a complex system can be freely coupled at different levels, forming a dynamic collaborative relationship, thereby endowing the system with stronger adaptability and intelligent emergence potential.
Applying the DIKWP model in the medical field helps to comprehensively understand the cognitive full-process of doctor-patient decision-making, and based on this, design a proactive and intelligent health intervention mechanism. One of its most distinctive elements is the "Semantic Tension—Purpose Guidance" mechanism. So-called "semantic tension" refers to the phenomenon of inconsistency or conflict between information at different levels in the cognitive network. For example, the data layer and information layer of the patient may show that blood pressure is rising, but the knowledge layer (the result expected by the doctor based on experience) believes that the patient's blood pressure should be controlled after taking medication—the discrepancy between the two creates semantic tension, that is, the difference between expectation and reality. Another example, the patient's self-feeling (wisdom layer) is inconsistent with objective test indicators (data layer), which is also a manifestation of semantic tension. The network structure of the DIKWP model allows this contradiction to be quickly captured and trigger feedback adjustment within the network. For example, when semantic tension is detected, the doctor may re-evaluate the treatment plan based on this (adjustment from the knowledge layer to the wisdom layer), or the AI system may prompt the-patient to re-measure their blood pressure to verify the data (feedback from the wisdom layer to the data layer). Semantic tension drives the self-renewal of the cognitive network, ensuring that the system does not operate blindly under false assumptions. Proactive medicine attaches great importance to this mechanism, because many medical errors and delays are precisely due to information asymmetry or model deviation; if the system can "perceive" the tension in the cognitive process and automatically solve it, the quality and safety of decision-making can be significantly improved.
Complementing semantic tension is the "Purpose Guidance" mechanism at the top of the DIKWP model. In the cognitive network, the highest-level Purpose represents the core goals and value orientation of the patient and medical decisions, such as "prolonging life," "improving quality of life," "maintaining dignity," etc. Traditional medical decisions often focus too much on the improvement of physiological indicators and ignore the patient's ultimate concerns, with the result that even if the disease control effect is good, the patient may still be dissatisfied with their state of life. The introduction of the Purpose layer is precisely to solve this problem: it provides a criterion and direction guide for the entire cognitive network. When semantic tension appears in the cognitive network and a decision needs to be made on how to adjust, the system must refer to the "general direction" given by the Purpose layer to choose a solution. For example, for the blood pressure control example mentioned earlier, if the patient's Purpose is "not to excessively affect the quality of life in order to lower blood pressure," then the doctor, when adjusting the treatment, may be inclined to increase lifestyle interventions such as exercise and diet, rather than simply relying on increasing the drug dosage—although the latter may be more effective in lowering the blood pressure numerically, it violates the patient's wish of "quality of life first." Another example, for a patient with advanced cancer, objective data and medical knowledge may suggest that chemotherapy still has a certain effect on prolonging life, but if the patient's Purpose is to "die peacefully rather than blindly prolonging life," then the wisdom layer will respect their wishes when making decisions and abandon high-intensity chemotherapy in favor of palliative care. It can be seen that the Purpose layer is like the "soul" of the cognitive network, injecting humanistic value constraints into the entire processing process from data to wisdom, ensuring that the final decision is not a cold algorithmic optimal solution, but the optimal solution that is truly "meaningful" to the patient.
In practical applications, the "Semantic Tension—Purpose Guidance" mechanism ensures that AI, doctors, and patients form a benign interaction and maintain alignment in values. On the one hand, the AI system can act as a keen detector and preliminary processor of semantic tension: when massive health data flows into the system, the AI model will continuously compare the fit between the new data and the existing knowledge model. Once an abnormal deviation (tension appears) is found, it will immediately issue an alarm or try to automatically adjust the model parameters. In this way, many subtle risk signals (such as an increase in negative words in the patient's language communication, suggesting an increase in depressed mood) that might be overlooked in traditional medicine can now be captured and processed by AI in time. On the other hand, humans play the final helmsman role at the Purpose layer: no matter what suggestions AI proposes, doctors and patients will make choices based on human value judgments. In this architecture, AI is no longer an incomprehensible "black box," but a transparent partner that can participate in discussions—it presents the detected tension and the given suggestions to doctors and patients in an explainable form, and humans make the final decision in combination with the Purpose layer information. In this way, the decision-making process becomes transparent, responsibilities are clear, and the risks of AI overstepping its duties or humans blindly following machine suggestions are avoided. Practical cases show that when an AI decision support system fully explains the basis of its suggestions to doctors and allows patients to participate in setting health goals, the trust and acceptance of AI by both doctors and patients will be significantly improved; as Topol et al. said, endowing AI with explainability and the ability to negotiate with people helps to elevate medical decision-making to a new realm of "human-machine integration."
A typical DIKWP model workflow can illustrate how semantic tension and Purpose guidance run through medical decision-making: First, collect the patient's raw health data (symptoms, self-measured indicators, test results, etc.) at the data layer, the information layer preliminarily classifies and interprets the data, and the knowledge layer compares and analyzes the information with the medical knowledge base to form a judgment on the health state. If it is found in this process that the data does not conform to the prediction of the knowledge base (tension appears), AI will generate alternative solutions at the wisdom layer (such as suggesting additional examinations, adjusting initial assumptions, etc.) and submit them to the doctor for reference. Subsequently, the doctor communicates and discusses with the patient, and after fully considering the patient's wishes (Purpose layer), makes a final decision at the wisdom layer and puts it into practice, and then observes the new data feedback, entering the next cycle. Every time a semantic tension is discovered and successfully resolved, the entire cognitive network completes a closed-loop optimization, and the patient's health management thus becomes more adaptive and individualized: the system not only uses all available data and knowledge to improve the scientific rigor of decision-making, but also ensures that all decisions are consistent with the patient's subjective Purpose and values. This precisely achieves the ideal pursued by proactive medicine—letting technology and humanities dance together, intelligence and ethics advance side by side, and improving the intelligence of medicine while ensuring a patient-centered value orientation.
It is worth noting that in recent years, there have been studies attempting to apply the DIKWP model to medical practice, to bridge the cognitive gap between doctors and patients and improve decision-making consistency. For example, in response to the problem of information asymmetry in the doctor-patient communication process, some scholars collected dialogue texts between doctors and patients in clinical outpatient clinics and constructed DIKWP semantic models for both doctors and patients. By capturing the external statements and internal thinking of doctors and patients in their communication, they uniformly mapped the interaction between the two parties to the five levels of data, information, knowledge, wisdom, and Purpose, and proposed a Purpose-driven DIKWP semantic fusion method to resolve uncertainty. The results showed that this method significantly improved the transparency and explainability of the medical process, and could effectively narrow the cognitive gap between doctors and patients and reduce decision-making differences caused by non-transparent information. This practical case proves the application potential of DIKWP theory in real-world medical scenarios, and also indicates that the proactive medicine information system will pay more attention to semantic-level interoperability and Purpose-driven intelligent decision-making optimization in the future.
In general, the networked cognitive structure presented by the DIKWP model, coupled with the "semantic tension" trigger mechanism and the "Purpose guidance" criterion, provides a paradigm for an intelligent and humanized medical information system for proactive medicine. On the one hand, this paradigm endows medical AI with a certain "cognitive emergence" ability: AI can autonomously discover new patterns and contradictions from massive data, and achieve self-evolution by continuously correcting internal models. On the other hand, it also ensures that artificial intelligence is always controlled by the human value framework set by the Purpose layer, and acts within safe boundaries, reflecting the ethical self-discipline of "technology for good." This balance between technological innovation and value constraints makes the information system of proactive medicine both have strong innovation vitality and maintain reliable controllability. Looking to the future, with the explosive growth of medical knowledge and the increasing diversity of patient needs, the DIKWP model can be further expanded—for example, by incorporating the public interest Purpose of group health, or the sustainable Purpose of ecological health, etc.—to build a grander multi-level Purpose system, to guide medical decision-making towards the optimization of broader health and well-being from multiple levels of individual, society, and environment. It can be seen that the DIKWP cognitive structure not only provides a solid ontological foundation and regulatory logic for proactive medicine, but also shows the theoretical tension of interdisciplinary integration and autonomous innovation: it integrates the scientific rigor of data-driven and the humanistic care centered on Purpose, heralding the huge potential of a new generation of health paradigms.
Conclusion
As can be seen from the above discussion, the "entropy structure of health and the principle of information-energy consistency" constitute the ontological foundation and the main line of regulatory logic of the proactive medicine theoretical system. Proactive medicine breaks through the narrow framework of the traditional disease-centered approach, defines health as a highly ordered state of the life system in the dual dimensions of material-energy and information-cognition, and emphasizes the maintenance of this order through the continuous input of negative entropy and information-energy coordination. Health means a low-entropy, orderly self-organizing steady state; disease means the out-of-control increase of entropy and the disintegration of order. Therefore, proactive medicine elevates the mission of medicine to "life entropy management," requiring doctors to pay attention not only to local lesions, but also to the maintenance of the overall system order. Through proactive preventive intervention to reduce entropy increase and introduce negative entropy, the body is always guided to evolve in a stable and orderly direction.
What is particularly important is that proactive medicine creatively integrates interdisciplinary ideas such as information theory, systems science, biocybernetics, and artificial intelligence, and connects physiology and psychology, individuals and the environment, humans and machines into a whole with the information field-energy field collaboration and the DIKWP intelligent architecture as the bridge. On the one hand, the principle of information-energy consistency ensures that we coordinate mind-body synchronization and the unity of knowledge and action in any health intervention, avoid "treating the head when the head aches, and treating the foot when the foot hurts," fundamentally reduce system entropy, and enhance the self-organization ability of life. On the other hand, the introduction of the DIKWP cognitive model enables us to deepen our cognition and regulation of the complex health system with the help of artificial intelligence: it transforms massive data into meaningful information and knowledge, and integrates human value Purpose into wisdom-based decision-making, achieving the organic integration of "technology and humanities." It is foreseeable that with the development of science and technology, proactive medicine will continue to enrich its theoretical and practical connotations, building information-energy coordinated health intervention strategies from the molecular network to the social ecology levels, and truly promoting the leap of the medical paradigm from passive treatment to proactive health, and from empirical art to intelligent science.
In summary, proactive medicine, with the entropy structural model of health as its cornerstone, runs through the core principle of information-energy consistency, and achieves the shaping and maintenance of the orderly order of life through negative entropy regulation and a Purpose-driven intelligent system. It marks a profound innovation in the health paradigm: from focusing on disease to focusing on the construction of global health order, from passive response to proactive intervention, from fragmented specialization to holistic integration. This theoretical framework not only deepens our understanding of the essence of life and health, but also points out the direction for future medical practice—that is, to use interdisciplinary wisdom, mobilize the synergistic effect of information and energy, to stimulate the potential of every life system to self-optimize and self-order, so as to maximize human health and well-being.
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