Artificial intelligence in psychiatry, present trends, and challenges: An updated review

Abstract

Abstract Artificial intelligence (AI) represents a revolutionary fusion of computer science and human-like problem-solving capabilities. In medicine, AI promises transformative changes, automating medical documentation, streamlining health insurance processes, and enhancing medical image analysis. The rising prevalence of mental illness across the world underscores the need for AI in psychiatry, where innovative approaches, such as speech analysis and real-time mental health assessments, are emerging. However, challenges loom. AI’s performance in radiology remains inconsistent. Biased training data, workflow disruptions, and a lack of validation standards pose hurdles. Speech recognition systems suffer from word errors, impacting clinical notes’ accuracy. The black-box nature of AI algorithms and their opacity in clinical settings require attention, particularly in safeguarding patient safety. Establishing guidelines for responsible AI use in mental health, addressing confidentiality, and handling critical situations is crucial. In conclusion, while AI holds immense promise in revolutionizing psychiatry and medicine, recognizing and addressing its challenges is imperative for its responsible and effective integration into clinical practice.

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