透明度(行为)
临床决策支持系统
检查表
决策支持系统
计算机科学
医疗保健
自闭症
心理健康
人工智能
医学
心理学
精神科
经济
经济增长
计算机安全
认知心理学
作者
Anne‐Kathrin Kleine,Eesha Kokje,Pia Hummelsberger,Eva Lermer,Insa Schaffernak,Susanne Gaube
标识
DOI:10.1016/j.artmed.2024.103052
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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