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

IF 6.1 2区医学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence in Medicine Pub Date : 2025-02-01 DOI:10.1016/j.artmed.2024.103052

Anne-Kathrin Kleine , Eesha Kokje , Pia Hummelsberger , Eva Lermer , Insa Schaffernak , Susanne Gaube

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Abstract

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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用于精神卫生保健的人工智能临床决策支持工具：产品综述。

该审查旨在提高用于精神卫生保健的受监管的人工智能临床决策支持系统（AI-CDSS）可用性的透明度。从84个潜在产品中，有7个符合纳入标准。这些产品可以分为三个主要领域：基于临床病史、行为和眼动追踪数据的自闭症谱系障碍（ASD）诊断；基于会话数据的多种疾病诊断以及基于临床病史和基因数据的药物选择。我们找到了五篇科学文章来评估设备的性能和外部有效性。报告的平均完整性，通过52%的遵守报告试验综合标准人工智能（consortium - ai）检查表来表示，是适度的，表明报告质量有改进的空间。我们的研究结果强调了获得监管机构批准、坚持科学标准以及紧跟监管环境最新变化的重要性。完善人工智能cdss的监管准则和实施有效的跟踪系统可以提高该领域的透明度和监督。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Artificial Intelligence in Medicine 工程技术-工程：生物医学

CiteScore

15.00

自引率

2.70%

发文量

143

审稿时长

6.3 months

期刊介绍： Artificial Intelligence in Medicine publishes original articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI) in medicine, medically-oriented human biology, and health care. Artificial intelligence in medicine may be characterized as the scientific discipline pertaining to research studies, projects, and applications that aim at supporting decision-based medical tasks through knowledge- and/or data-intensive computer-based solutions that ultimately support and improve the performance of a human care provider.