THE CRITICAL NEED FOR PSYCHIATRY Author: Abraham Peled M.D.

In September 2024, I have been approached by numerous startup companies aiming to improve mental health diagnosis and treatment. This surge of activity stems from two primary factors: 1) an increasing gap between need and available services in this field, and 2) the advent of new technologies, particularly artificial intelligence (AI).

These companies typically focus on developing similar capabilities, primarily:

1. Creating AI models to assist clinicians with their workload. These models are designed to simulate and emulate the work of mental health professionals. This approach also extends to therapeutic chatbots, again with the goal of reducing clinician workloads.
2. Implementing remote digital monitoring using wearables and other sensors to extract, record, and track clinical phenomenology, thereby supplementing or potentially replacing certain clinician functions. This remote clinical phenotyping complements telepsychiatry, which has been in use for over a decade.

While these efforts are commendable, a CRITICAL need in psychiatry remains unaddressed. This fundamental requirement is so essential that without it, progress in the field using current technologies will be limited. AI efforts should first be directed towards this fundamental need before any significant advancements can be made.

What is this critical need? It is the necessity to understand WHAT is WRONG with our patients. In medical terms, this is referred to as 'etiology' - the cause of mental disorders.

To illustrate this point, let's compare two clinical scenarios:

1. A patient visits a physician complaining of stomach pain. The doctor conducts clinical tests and diagnoses appendicitis, indicating that the appendix (a specific location in the intestine) is infected. This diagnosis is etiological because the name of the disease identifies its cause.
2. In contrast, when a patient consults a psychiatrist about feeling depressed and asks, "Doctor, what do I have?", the answer is often simply "Depression." A perceptive patient might think, "I just told you that. I said I was depressed, and you're telling me I'm depressed?" There's an implicit expectation that the psychiatrist will identify the cause of the depression in that patient. However, "Depression" doesn't refer to a specific location in the body or a known pathological mechanism. In psychiatry, these underlying causes are largely unknown.

This lack of etiological understanding in psychiatry is critical. Without knowing what's fundamentally wrong with our patients, how can we ever hope to help or cure them effectively? Discovering the etiology (causes) of mental disorders is the primary critical NEED in psychiatry. Without this knowledge, all other current efforts are essentially variations on existing approaches, likely to yield the same poor treatment efficacy that has long characterized mental health care.

Neuromodulation technology (i.e., brain pacemakers) is rapidly advancing. Soon, psychiatrists will be asked to define the exact algorithm of brain disturbances affecting their patients, much like cardiologists need to understand cardiac arrhythmias to apply the appropriate cardiac pacemaker to correct the condition and cure the patient.

The era of descriptive, "brainless" conceptualizations of mental disorders should be coming to an end. A novel, brain-related conceptualization should take its place as an etiological diagnostic system. The most promising path forward is to apply cutting-edge neuroscience discoveries to psychiatric phenomenology. For over 30 years, I have been working precisely on this, integrating new neuroscience findings with psychiatric phenomenology. Specifically, I've utilized mathematical models of the brain, a field known as Neural Computation, which is closely related to AI as it is based on neuronal network algorithms mirroring brain architecture.

After three decades of theoretical and practical research, I have successfully translated psychiatric phenomenology into etiological frameworks for mental disorders. This work includes the development of testable hypotheses, culminating in a comprehensive perspective on the field. I have formulated brain-related coordinates in time and space to elucidate the spectrum of psychiatric phenomenology, an approach I have termed 'Neuroanalysis' and 'Brain Profiling'. Detailed information about this work is available at https://www.brainprofiler.online/ .

Figure 1 provides a general overview of how psychiatric phenomenology has been reconceptualized into brain space-time algorithmic coordinates.

The current surge of interest in AI applications for mental health presents a valuable opportunity to advance 'Neuroanalysis'. By integrating this approach into an AI-driven discovery platform, we can create a unique initiative that stands apart from other efforts in the field. The organization that chooses to incorporate Neuroanalysis into their work has the potential to achieve a significant breakthrough in psychiatry, potentially leading to unparalleled commercial success.

contact me at: [email protected]