We've mentioned that AI can assist with diagnosis, but is that really true?

Diagnosis in behavioral health has long been fraught with challenges, with misdiagnosis not uncommon. This is due to overlapping symptoms and co-morbidities. For example, a patient experiencing low mood and insomnia might have depression, an anxiety disorder, or something else entirely, like a reaction to stress at work. Similarly, distinguishing whether depression is causing drug abuse or vice versa is complex. Symptoms can also vary by age, gender, and the stage of the condition, making absolute certainty in diagnosis difficult.

These complexities extend to AI, as it learns from existing human-created content, reflecting the current state of the field. So, how can AI assist practitioners in diagnosis?

AI assists, rather than replaces, the practitioner. It processes session content and notes, providing additional data and suggestions. AI can identify hidden patterns, make connections, and tap into vast databases on psychological conditions or biological markers. It can analyze facial expressions, language quirks, and tone of voice, fitting them into established patterns that hold clues to a patient’s condition.

While AI won't bring instant certainty to an evolving field, it expands and sharpens the data available to therapists, enhancing their ability to diagnose accurately. This ultimately benefits the patient, providing a more comprehensive and informed approach to their care.