Generative Artificial Intelligence-based Clinical Decision Support in Patient Data Collection and Analysis, in Physiological Parameter Monitoring, and in Image-based Disease Diagnosis
Generative Artificial Intelligence-based Clinical Decision Support in Patient Data Collection and Analysis, in Physiological Parameter Monitoring, and in Image-based Disease Diagnosis

Summary/Abstract: We draw on a substantial body of theoretical and empirical research on how ChatGPT is instrumental in clinical decision support, in medical record abstraction, and in treatment recommendation provision by inspecting massive quantities of patient data, that is an emerging topic involving much interest. In this research, prior findings were cumulated indicating that generative artificial intelligence technologies can assist in timely and accurate clinical diagnosis procedures and treatment planning, and in medical knowledge and support. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2023, with search terms including “generative artificial intelligence-based clinical decision support” + “patient data collection and analysis,” “physiological parameter monitoring,” and “image-based disease diagnosis.” As we analyzed research published in 2023, only 173 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 44, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR.

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