Kleine, AK; Lermer, E; Cecil, J; Heinrich, A; Gaube, S; (2023) Advancing mental health care with AI-enabled precision psychiatry tools: A patent review. Computers in Human Behavior Reports , 12 , Article 100322. 10.1016/j.chbr.2023.100322.

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Abstract

The review provides an overview of patents on AI-enabled precision psychiatry tools published between 2015 and mid-October 2022. Multiple analytic approaches, such as graphic network analysis and topic modeling, are used to analyze the scope, content, and trends of the retained patents. The included tools aim to provide accurate diagnoses according to established psychometric criteria, predict the response to specific treatment approaches, suggest optimal treatments, and make prognoses regarding disorder courses without intervention. About one-third of the tools recommend treatment options or include treatment administration related to digital therapeutics, pharmacotherapy, and electrotherapy. Data sources used to make predictions include behavioral data collected through mobile devices, neuroimaging, and electronic health records. The complexity of technology combinations used in the included devices has increased until 2021. The topics extracted from the patent data illuminate current trends and potential future developments in AI-enabled precision psychiatry. The most impactful patents and associated available products reveal relevant commercialization possibilities and likely future developments. Overall, the review highlights the potential of adopting AI-enabled precision psychiatry tools in practice.

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