AI-enabled clinical decision support tools for mental healthcare: A product review

被引：1

作者：

Kleine, Anne-Kathrin ^{[1
]}

Kokje, Eesha ^{[1
]}

Hummelsberger, Pia ^{[1
]}

Lermer, Eva ^{[1
,2
]}

Schaffernak, Insa ^{[2
]}

Gaube, Susanne ^{[3
]}

机构：

[1] Ludwig Maximilians Univ Munchen, Geschwister Scholl Pl 1, D-80539 Munich, Germany

[2] Tech Univ Appl Sci Augsburg, Augsburg, Germany

[3] UCL, London, England

来源：

ARTIFICIAL INTELLIGENCE IN MEDICINE | 2025年 / 160卷

关键词：

Artificial intelligence; Mental healthcare; Clinical decision support; Medical device regulation; MEDICAL DEVICES; ARTIFICIAL-INTELLIGENCE; PRECISION PSYCHIATRY; ILLNESS; EUROPE; RISK;

D O I：

10.1016/j.artmed.2024.103052

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The review seeks to promote transparency in the availability of regulated AI-enabled Clinical Decision Support Systems (AI-CDSS) for mental healthcare. From 84 potential products, seven fulfilled the inclusion criteria. The products can be categorized into three major areas: diagnosis of autism spectrum disorder (ASD) based on clinical history, behavioral, and eye-tracking data; diagnosis of multiple disorders based on conversational data; and medication selection based on clinical history and genetic data. We found five scientific articles evaluating the devices' performance and external validity. The average completeness of reporting, indicated by 52 % adherence to the Consolidated Standards of Reporting Trials Artificial Intelligence (CONSORT-AI) checklist, was modest, signaling room for improvement in reporting quality. Our findings stress the importance of obtaining regulatory approval, adhering to scientific standards, and staying up-to-date with the latest changes in the regulatory landscape. Refining regulatory guidelines and implementing effective tracking systems for AI-CDSS could enhance transparency and oversight in the field.

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页数：11

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