Towards Metaclinical Medicine　― The Non-Human Physician as Our Destiny ―

Abstract

Medicine, and human healing more generally, have been constantly evolving for millennia as part of humanity’s persistent efforts to heal its injuries and diseases, to maintain wellbeing, and to delay the inevitable: death. The philosophy underlying medicine has always been closely intertwined with the prevailing ideas in each historical period. Prejudices, religious beliefs, even magical herbs, as well as rational thought and advanced sciences, make up the fabric of over 2,000 years of western medicine. Hippocrates (460–377 BC), a physician from ancient Greece, is considered the father of western medicine. Almost 2,000 years later, Andreas Vesalius (1514–1564), by being the first to explore anatomical dissections of humans, significantly challenged the views of Galen, thus ushering in modern medicine, which, by the mid-19th century, had evolved into clinical medicine, a holistic approach that remains relevant today. The rapid advances in artificial intelligence, and more broadly in digital health, are shifting clinical medicine towards a new perspective, that of metaclinical medicine, where human doctors will need to work closely with non-human physicians, delegating a significant part of their traditional role in diagnosis and treatment. This article outlines the existing realities regarding the role of artificial intelligence in diagnosing various diseases, and speculates on the collaboration between human and non-human physicians in the metaclinical era.

Medicine, an ever-evolving blend of science, art, and experience, must constantly adapt to the circumstances and developments of each new era. Over centuries, medicine has been painstakingly constructed on the solid foundations of research and evidence-based practice, with major strides in biotechnology, pharmacology, genetics, informatics, and materials science serving as significant catalysts.

Today, the physician’s armamentarium contains advanced cardiac imaging, numerous biomarkers, and groundbreaking genome analysis tools, enhancing diagnostic and therapeutic processes. Yet, despite these powerful tools, the physician’s role remains central in determining the final diagnosis and treatment. This decisive role, a hallmark of “clinical medicine” since its establishment in the mid-19th century, is rooted in hospital care, and emphasizes direct interaction with the patient, detailed observation, and the application of clinical knowledge tailored to each patient’s needs.

However, the landscape of medicine is currently undergoing a rapid transformation in response to the impact of digital health and the extraordinary capabilities of artificial intelligence (AI). These advances are poised to push medical sciences and care beyond human comprehension, ushering in the era of “metaclinical medicine.”¹ In this new era, the human physician’s role is likely to be diminished, as advanced AI takes over critical data analysis and synthesis, including genomic, imaging and biochemical information. Indeed, the term “metaclinical medicine” introduced by Vardas et al.¹ refers to the full range of diagnostic and therapeutic medical science that will increasingly rely on digital technologies, particularly AI, with human involvement in observations and decision making becoming progressively less central and decisive. Although this shift may seem unthinkable to those anchored in traditional reasoning, it reflects the magnitude of the forthcoming changes.

This new age of medicine, which could be called the “metaclinical era,” marks the opening of the latest historical chapter, the culmination of 3 main phases of Western medicine, stretching from Hippocrates to today and beyond, as presented schematically in the Figure.

Figure.

The 25-century evolution of Western medicine, from Hippocrates to clinical, and even beyond to metaclinical, medicine. Adapted from Vardas PE, et al.¹

Paradigms of AI Outperforming Traditional Human-Driven Medicine

The interaction between AI and clinical medicine is becoming a highly significant issue that will inevitably define and profoundly impact the entire concept of clinical practice and healthcare. The first scientific publications and applications are already revealing the magnitude of current and potential developments. Below are some brief examples of areas where clinical practice is already demonstrably supported by decision-making algorithms.

Diagnostics and Imaging

Diagnostic imaging is a key field that shows the potential of AI to outperform human-driven medicine. Algorithms based on deep learning are capable of evaluating medical images, including mammograms, computed tomography, and magnetic resonance imaging scans, with extraordinary accuracy. In one study published a couple of years ago,² an AI model applied to breast cancer screening was able to reduce the rate of false negatives by 9.4% in the US and by 2.7% in the UK, detecting many cases of breast cancer that were missed by traditional radiologists.²

Similarly, Google’s AI system, DeepMind, has been shown in a number of ophthalmology studies to have an impressive ability to diagnose retinal diseases, such as diabetic retinopathy and age-related macular degeneration (AMD), identifying the presence of disease faster and with greater precision than human specialists.³

Predictive Analytics and Personalized Medicine

The ability of AI to process vast amounts of data in a short time frame allows it to make a key contribution to predictive analytics and personalized medicine. Whereas traditional human-driven medicine tends to be rooted in generalized treatment protocols, AI can rapidly analyze genetic information, electronic health records, and even lifestyle data so as to tailor treatments to individual patients. For example, AI systems trained in oncology may be able to predict the progression of cancer or the likelihood of recurrence based on a patient’s unique genetic profile. One such system, developed by IBM’s Watson Health, has been programmed to recommend personalized cancer treatments, analyzing the latest medical literature alongside patient data to come up with treatment recommendations that go beyond the expertise of any single physician.^4,5

In a different context, a study from the Massachusetts Institute of Technology (MIT) found that AI was able to predict patient mortality in intensive care units more effectively than human doctors.⁶ After analyzing vital signs, laboratory, results and other data points, the AI system could predict which intensive care unit patients were at the highest risk of death within the next 48 h, enabling clinicians to intervene earlier and potentially saving lives.⁶

AI in Surgical Procedures

AI is also making its presence felt in surgery, where human expertise and manual dexterity have long been prized above all else. Now, robots like the da Vinci Surgical System are revolutionizing surgical interventions, demonstrating a level of precision beyond human ability.⁷

Although these systems still depend on human guidance, AI is also showing it can play a prominent supporting role in planning and executing procedures. AI is able to create detailed 3-dimensional models of a patient’s anatomy, assisting surgeons in planning more precise complex procedures.⁸

AI has even been used to guide autonomous robotic surgeries, performing parts of the operation with minimal human intervention. This opens the door to the specter of entirely automated surgery, in which AI can outperform human surgeons in terms of speed, precision, and consistency, at least for routine procedures.

AI in Healthcare Administration

Administrative tasks in healthcare, including the management of patient records, scheduling, billing, and insurance claims, can be time-consuming and vulnerable to human error. Apart from its clinical applications, AI may also contribute to improving healthcare administration by automating these tasks, reducing errors, and, at the same time, freeing healthcare professionals to focus on patient care.

Examples of this new role include the transcription and analysis of physician–patient interactions by natural language processing algorithms, allowing electronic health records to be created and/or updated automatically, without the need for human input. Thus, doctors are able to spend more time with their patients rather than dealing with administrative duties, while at the same time the accuracy and consistency of computer records are enhanced.⁹

AI in Drug Discovery

Traditional drug discovery involves time-consuming and costly procedures, and bringing a new drug to market often requires years or even decades of research and trials. However, AI is able to identify potential drug therapies much faster than human researchers through the analysis of vast datasets of chemical compounds, biological interactions, and patient-specific information. By sifting through millions of molecular compounds to determine which are most likely to interact with a specific target, AI can significantly cut down the time required for preclinical research.

During the recent COVID-19 pandemic, AI’s ability to analyze vast amounts of data enabled it to quickly pick out drugs and chemical compounds that may be repurposed to treat the virus. This allowed researchers to identify potential treatments far more quickly than using traditional methods.^10,11

These examples demonstrate how AI is rapidly outperforming traditional human-driven medicine in roles that span diagnostics, personalized medicine, surgery, drug discovery, and healthcare administration (Table). If this trend continues, the AI-enabled non-human physician may be able to take over a significant portion of medical practice, progressively limiting the role and participation of the human physician in the diagnosis and treatment of patients.

Table.

AI-Based Medicine and Its Various Applications

AI application	Description	Examples of use in medicine
Medical imaging	AI algorithms analyze medical images for a faster and more accurate diagnosis	Detecting cancer (mammograms, CT scans), brain injuries (MRI), and retinal diseases
Predictive analytics	AI predicts patient outcomes based on historical data and trends	Predicting heart disease risk, hospital readmission rates, and personalized treatment
Drug discovery	AI accelerates the discovery and development of new drugs by analyzing biological data and molecular structures	Identifying potential drugs for diseases like COVID-19, Alzheimer’s disease, and cancer
Clinical decision support	AI assists physicians by providing evidence-based suggestions for diagnosis and treatment	Recommendations for medication, identifying the best treatment protocols for conditions like sepsis
NLP	AI extracts insights from clinical notes and the literature by processing and understanding text	Automating clinical documentation, summarizing patient records, and literature reviews
Genomics and personalized medicine	AI analyzes genetic data to tailor treatments to individual patients based on their unique genetic profile	Identifying patients at risk for genetic disorders, guiding cancer treatment (precision oncology)
Robotic surgery	AI-powered robots assist surgeons in performing complex surgeries with enhanced precision	Robotic-assisted heart surgery, prostate surgery, and minimally invasive procedures
Wearables and remote monitoring	AI analyzes data from wearables to monitor patient health in real-time, allowing for proactive intervention	Detecting arrhythmias, glucose monitoring in diabetes, and monitoring vital signs in chronic disease
Virtual health assistants	AI-powered virtual assistants help patients manage their health and provide advice	Virtual chatbots for symptom checks, medication reminders, and patient education
AI in clinical trials	AI helps design, recruit, and analyze data from clinical trials more efficiently	Accelerating recruitment, predicting trial outcomes, and optimizing data analysis
AI in EHR	AI automates routine tasks within EHRs, reducing physician burnout and improving data entry accuracy	Automated coding, charting, and patient summaries

AI, artificial intelligence; CT, computed tomography; EHR, electronic health records; MRI, magnetic resonance imaging; NLP, natural language processing.

Human vs. Non-Human Physician: A Speculative Analysis

The above observations regarding the rapid evolution of AI-driven medicine suggest a need for a comparative evaluation of the human vs. non-human physician, the capabilities and limitations of each, while taking into account potential ethical dilemmas, along with regulatory and legal issues.

Without being able to so far well objectivize and define the term “non-human physician,” we propose for the time being the following definition: a “non-human physician” could refer to an advanced AI or robotic system capable of performing diagnostic, therapeutic, and decision-making tasks typically performed by human doctors. These systems use algorithms and data processing for medical care and, over time, may gain recognition from regulatory authorities to autonomously perform certain diagnostic or therapeutic actions without human oversight, becoming a decisive entity in specific medical interventions. Their evolving role could reshape the landscape of healthcare.

Human Physicians: Empathy and Ethical Judgment

Human physicians possess qualities that machines are thus far unable to replicate. Medical practice is more than just a science; it is also an art that often demands emotional intelligence, empathy, and ethical judgment. Despite AI’s impressive ability to diagnose diseases, it is not capable of addressing the subtleties of a patient’s emotional and psychological state. Apart from medical advice, patients also expect their doctors to provide reassurance and express compassion, and, given the current state of the art, these are services that an AI cannot provide.

And then there is the ethical dimension. Moral dilemmas, such as balancing the risks and benefits of treatment options or dealing with end-of-life care, are a common preoccupation for the clinical physician, for whom the ability to manage these sensitive issues with a view to the patient’s wellbeing is essential. Although non-human physicians may easily be able to list the available options, they lack the lived human experience on which such nuanced decision making must be based.¹²

Ethical and Social Implications

The specter of the non-human physician brings with it some major ethical issues. Should an AI system be held responsible if it makes a mistake? If not, then who is responsible? Can we be sure that AI will be used equitably, or could it perpetuate (or even worsen) existing healthcare disparities? Furthermore, because AI systems rely on vast amounts of personal data in order to function effectively, how can we guarantee patients’ privacy?¹³

There are also more personal aspects to consider: will patients trust a non-human physician? Certainly, some of them will be impressed by the precision and efficiency that AI offers, but granting control of their health to a machine may be a step too far for others. If patients feel that the new technology is taking over responsibility for their care, the trust and communication on which the doctor–patient relationship should be founded could be undermined.¹⁴

The Next Generation of AI-Augmented Human Physicians

The next generation of physicians will need to be ready to make use of the best of both human expertise and AI. The degree to which AI algorithms will replace the physician’s decisive role in diagnostic and therapeutic decisions is not entirely predictable today. However, it seems likely that, over the course of 1 or 2 decades, generative AI models will play a significant role in the comprehensive management of patients. It seems exceedingly premature, and perhaps unattainable, to claim that a non-human physician could fully replace the human doctor in healing the patient, because human empathy, psychological communication, and physical interaction with the patient render human presence indispensable and irreplaceable. Based on the above, the evolutionary process in this innovative coexistence, which will henceforth characterize the metaclinical era, could be envisaged as described below.

AI-Augmented Physicians

Physicians of the next few decades will routinely use AI to assist with diagnostics, treatment planning, and decision making, using its ability to accurately analyze vast quantities of medical images, genetic data, and patient histories much faster than any human doctor can. Indeed, AI’s enormous capacity for Big Data classification and analysis is expected to play a vital role in personalized medicine, making it a progressively routine practice in cardiovascular care.¹⁵

Human Focus on Empathy and Ethics

As noted above, no matter how proficient AI becomes at data analysis, one thing it cannot offer is empathy or real understanding, qualities that are central to healthcare. Even the most imaginative minds may find it unlikely that AI could entirely replace doctors in their interaction with patients, despite its catalytic and decisive involvement in patient management and care.¹⁶

AI-Powered Preventive Medicine

The next-generation physician will also be able to favor a more proactive approach to healthcare, using AI-driven predictive analytics to identify and address health risks before they develop into serious conditions.^17,18 Using AI to analyze real-time data from wearable health tech and electronic health records, doctors will be able to offer preventive interventions, such as lifestyle changes or early treatments, long before symptoms manifest.^19,20

Can Machines Heal the Soul? Speculations Beyond the Boundaries

The importance of the psychological aspect of medicine is well known to all physicians. Apart from pharmaceutical or interventional treatments, the patient’s emotional, spiritual, and psychological wellbeing plays a vital part in the healing process. Although AI shows incredible potential for diagnosing diseases, delivering personalized treatment, and even predicting illnesses, can we and should we expect it to be able to “heal the soul”? However superficially impressive its capabilities, can a computer program, which deep down is just crunching numbers based on a set of complex algorithms, truly address the more intangible dimensions of human life?

It should be stressed at this point that the capabilities we are talking about today would have seemed fantastic 2 decades ago, and we can only speculate about how they may have evolved after a further 2 decades or more. Thus, the opinions expressed here represent a snapshot taken at a particular moment in time, and leave open the possibility for dramatic developments, both within and beyond current constraints, in the near or distant future.

Machines in Healthcare: Precision Without Empathy

Healing the soul requires a depth of emotional sensitivity that can only be offered by human physicians, therapists, and spiritual guides based on their physical presence, empathy, and shared experience. Although today’s AIs can simulate conversation or provide psychological advice, based on sophisticated algorithms, such interactions are not backed by any feelings or real understanding.²¹ This makes it improbable that such software can connect with a patient’s emotional and existential struggles in any meaningful way. For many patients, healing is not only a physical process, but also requires the psychological support represented by genuine interaction with another person. This is a profoundly human need that machines cannot satisfy.²²

Human Connection as a Path to Healing

This kind of connection with another human being is a vital component of healing the soul. Either in the short term, in moments of vulnerability, or through therapeutic relationships over a longer period, a patient may take comfort from an understanding manner, or the awareness that another individual is there to support them. The personal doctor–patient relationship can meet patients’ deep needs for acknowledgment and support.

Algorithms, however sophisticated, cannot effectively replicate the complex emotional components of a human relationship. The experienced human physician can perceive involuntary signals involving body language, manner, and facial expressions to a degree far beyond the range of any machine. In addition, humans share common experiences of pain, joy, and existential questioning of which a non-conscious machine is completely unaware. Thus, the human connection provides dimensions of meaningful interaction that an AI cannot comprehend, much less engage in.²³

AI and Mental Health: Can Machines Provide Psychological Support?

In an attempt to address issues of mental health, AI-driven chatbots and virtual therapists, including the Woebot app and AI companions such as Replika, have been developed to offer psychological support through engagement with non-human entities. Some patients appear to find great comfort through the use of these tools, especially if no human therapist is available.

However, although these tools may be effective in certain contexts, it is questionable whether they can provide emotional support of sufficient quality and depth in the long term. Although software may be able to simulate empathy or provide the type of response used in cognitive behavior therapy, it does not possess the underlying motivation that drives the human therapist. The knowledge that another human cares about your wellbeing is a key element in emotional healing, and no machine can currently provide such reassurance.²⁴

Spirituality and the Soul: Beyond the Reach of AI

For many people, healing the soul is not simply a matter of mental health but also involves deeper spiritual and existential dimensions. Questions about meaning, purpose, and mortality often emerge in times of suffering. There may be moments when spiritual guidance, whether through religious practices, meditation, or philosophical inquiry, becomes essential.

Although machines may provide logical answers or suggest mindfulness techniques, they are inherently unable to guide individuals through such complex spiritual experiences. The spiritual journey is deeply personal, and the aspiring guide will often require a level of intuition, wisdom, and understanding that transcends data and algorithms. The realms of the soul that deal with existential meaning, purpose, and faith remain beyond the reach of AI.

The Role of Machines in Supporting, Not Replacing, Human Healing

Although machines cannot heal the soul, they may nevertheless be of value in supporting human healers. By providing data-driven insights, streamlining processes, and targeting treatments, AI and technology can assist physicians, therapists, and spiritual guides by reducing the burden of mundane tasks, allowing human caregivers to focus on connecting with patients on a deeper emotional level.

In this limited way, AI tools can offer preliminary support or help individuals manage their conditions, leaving human therapists to handle the more nuanced aspects of mental health care.²⁵ In the future, AI may be enlisted to deal with tasks that do not require empathy, allowing humans to provide the emotional and spiritual care of which the machines are incapable.

The Soul Remains Human

The soul, however it is defined, remains beyond the reach of machines. Whatever assistance AI and technology may offer in terms of physical health and mental wellbeing, true healing of the soul remains an essentially human domain that is founded on an empathetic presence and a shared understanding of life, suffering, and deeper meaning.

Metaclinical Medicine as a Response to Historical Limitations

Metaclinical medicine can be seen as a natural transition to a new level, where AI’s abilities in data analysis, based on the accumulation of huge amounts of medical data, will leave traditional human diagnostic and therapeutic interventions to take a back seat in most kinds of daily patient management.¹

Metaclinical medicine can also be seen as a response to the historical limitations of conventional medicine, particularly its tendencies towards reductionism and fragmentation of care. Although the concept of metaclinical medicine is still emerging, its roots are deeply historical, grounded in the ongoing evolution of medical practice towards more complex, data-driven, and human-centered approaches to health.

As healthcare continues to evolve, through the integration of clinical, genetic, technological, ethical, and holistic perspectives, metaclinical medicine represents a future that contains a more interconnected, patient-centered, and technology-enhanced type of medical practice.

Conclusions

The evolution of medicine is the result of constant effort by humans aimed at healing both the body and soul. The mindsets and tools of each medical era (i.e., religious beliefs, empirical therapies, scientific observations and discoveries) were enlisted to serve this continuing cause. We can be certain that the groundbreaking developments in digital health in general, and in AI in particular, will progressively and significantly encroach upon the diagnostic and therapeutic role of the human physician, turning over the page to a new chapter, the Age of Metaclinical Medicine.

Nevertheless, healing is a much broader concept than curing, encompassing a holistic approach to both body and soul. This must be kept in mind as we usher in the future, so that enhanced collaboration between humans and intelligent artificial beings can lead to a metamorphosis of the curing and healing process.

Disclosures

P.E.V. serves as a consultant to the European Society of Cardiology and the Hygeia Hospitals Group (HHG). The remaining authors have no conflicts of interest to declare.

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