Machine Learning for Mental Health: Applications, Challenges, and the Clinician's Role.

Purpose Of Review: This review aims to evaluate the current psychiatric applications and limitations of machine learning (ML), defined as techniques used to train algorithms to improve performance at a task based on data. The review emphasizes the clinician's role in ensuring equitable and effective patient care and seeks to inform mental health providers about the importance of clinician involvement in these technologies.

Recent Findings: ML in psychiatry has advanced through electronic health record integration, disease phenotyping, and remote monitoring through mobile applications.