Tijdschrift voor psychiatrie · 2025
[The role of artificial intelligence in psychiatric diagnosis and classification: A state-of-the-art review in an uncharted domain].
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Jaspers F A F, van Wingen G A, Jongsma K R, Bertens R M, Legerstee J S
Аннотация
BACKGROUND: The deployment of artificial intelligence (AI) is creating new opportunities for sophisticated classification and diagnosis across mainstream healthcare. Although the technology shows substantial promise, its translation into mental-health practice is hampered by a distinct set of additional challenges.
AIM: To elucidate the current state of AI-driven diagnostic methods within psychiatry.
METHOD: Reflective essay in which we as experts in psychiatry, AI technology, data innovation, ethics and jurisprudence combine our perspectives.
RESULTS: Technological progress is advancing more rapidly than clinical practice can absorb. Because supervised-learning algorithms and large-language models rely on robust, standardised labelling—something the present classificatory system still fails to supply consistently—large-scale clinical adoption remains limited. Moreover, the responsible use of AI calls for advanced technical, communicative and normative competencies among healthcare professionals, while simultaneously raising critical ethical questions. Until AI systems are purposefully developed for, or authorised under, medical regulations, a cautious legal stance is indispensable.
CONCLUSION: Once clinical, ethical and legal prerequisites have been satisfied, however, implementation and further refinement of AI tools promise swifter, more reliable and more objective psychiatric diagnosis, thereby paving the way for more efficient mental-health care.
AIM: To elucidate the current state of AI-driven diagnostic methods within psychiatry.
METHOD: Reflective essay in which we as experts in psychiatry, AI technology, data innovation, ethics and jurisprudence combine our perspectives.
RESULTS: Technological progress is advancing more rapidly than clinical practice can absorb. Because supervised-learning algorithms and large-language models rely on robust, standardised labelling—something the present classificatory system still fails to supply consistently—large-scale clinical adoption remains limited. Moreover, the responsible use of AI calls for advanced technical, communicative and normative competencies among healthcare professionals, while simultaneously raising critical ethical questions. Until AI systems are purposefully developed for, or authorised under, medical regulations, a cautious legal stance is indispensable.
CONCLUSION: Once clinical, ethical and legal prerequisites have been satisfied, however, implementation and further refinement of AI tools promise swifter, more reliable and more objective psychiatric diagnosis, thereby paving the way for more efficient mental-health care.