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

Journal: Psychiatry research
Published Date:

Abstract

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.

Authors

  • Christophe Gauld
    Department of Child Psychiatry, Université de Lyon, 59 Bd Pinel, Lyon 69 000, France; Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS, Université Claude Bernard Lyon 1, Lyon F-69000, France. Electronic address: christophe.gauld@chu-lyon.fr.
  • Vincent P Martin
    Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg; CNRS, Bordeaux INP, LaBRI, UMR 5800, Université de Bordeaux, Talence F-33400, France.
  • Hugo Bottemanne
    Paris Brain Institute - Institut du Cerveau (ICM), INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, DMU Neuroscience, Sorbonne University, Paris, France; Department of Psychiatry, Pitié-Salpêtrière Hospital, DMU Neuroscience, Sorbonne University, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France.
  • Pierre Fourneret
    Department of Child Psychiatry, Université de Lyon, 59 Bd Pinel, Lyon 69 000, France; Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS, Université Claude Bernard Lyon 1, Lyon F-69000, France.
  • Jean-Arthur Micoulaud-Franchi
    CNRS, SANPSY, UMR 6033, Université de Bordeaux, Bordeaux F-33000, France; University Sleep Clinic, University Hospital of Bordeaux, Place Amélie Raba-Leon, Bordeaux 33 076, France.
  • Guillaume Dumas
    Human Genetics and Cognitive Functions, Institut Pasteur, Université Paris Diderot, Sorbonne Paris Cité, CNRS UMR3571 / USR 3756, Paris, France.