Generative Artificial Intelligence-based Treatment Planning in Patient Consultation and Support, in Digital Health Interventions, and in Medical Practice and Education Cover Image
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Generative Artificial Intelligence-based Treatment Planning in Patient Consultation and Support, in Digital Health Interventions, and in Medical Practice and Education
Generative Artificial Intelligence-based Treatment Planning in Patient Consultation and Support, in Digital Health Interventions, and in Medical Practice and Education

Author(s): Diana Atkinson
Subject(s): Health and medicine and law, ICT Information and Communications Technologies
Published by: Addleton Academic Publishers
Keywords: ChatGPT; generative artificial intelligence; treatment planning; patient consultation and support; digital health interventions; medical practice and education;

Summary/Abstract: Despite the relevance of how generative artificial intelligence technologies can improve medical education by integrating immersive and contextually relevant realistic healthcare simulations and providing personalized feedback to digital patients, only limited research has been conducted on this topic. In this article, I cumulate previous research findings indicating that ChatGPT can manage intricate medical and clinical information in diagnosis, treatment planning, and patient outcome monitoring. I contribute to the literature on how generative artificial intelligence algorithms can deploy visual information related to high-level decision-making questions and produce consistent results in clinical applications by showing that ChatGPT can be pivotal in healthcare services, in medical education processes, and in clinical reasoning tasks with regard to preventative measures and treatment options. Throughout April 2023, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “generative artificial intelligence-based treatment planning” + “patient consultation and support,” “digital health interventions,” and “medical practice and education.” As I inspected research published in 2023, only 180 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 34, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Meth- odological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT.

  • Issue Year: 15/2023
  • Issue No: 1
  • Page Range: 134-151
  • Page Count: 18
  • Language: English