Exploring the interplay of clinical reasoning and artificial intelligence in psychiatry: Current insights and future...

For many years, it has been widely accepted in the psychiatric field that clinical practice cannot be reduced to finely tuned statistical prediction systems utilizing diverse clinical data. Clinicians are recognized for their unique and irreplaceable roles. In this brief historical overview, viewed through the lens of artificial intelligence (AI), we propose that comprehending the reasoning behind AI can enhance our understanding of clinical reasoning. Our objective is to systematically identify the factors that shape clinical reasoning in medicine, based on six factors that were historically considered beyond the reach of statistical methods: open-endedness, unanalyzed stimulus-equivalences, empty cells, theory mediation, insufficient time, and highly configured functions. Nevertheless, a pertinent consideration in the age of AI is whether these once-considered insurmountable specific factors of clinicians are now subject to scrutiny or not. Through example in AI, we demonstrate that a deeper understanding of these factors not only sheds light on clinical decision-making and its heuristic processes but also underscores the significance of collaboration between AI experts and healthcare professionals. This comparison between AI and clinical reasoning contributes to a better grasp of the current challenges AI faces in the realm of clinical medicine.