Scientometric analysis maps research trends on generative AI hallucinations and misinformation in healthcare, highlighting critical needs for clinical reliability and governance.
The rapid growth of generative artificial intelligence (AI) and large language models (LLMs) has significantly transformed healthcare and digital health systems, while simultaneously raising concerns regarding hallucinations, misinformation, trust, and reliability. This study conducts a scientometric analysis to examine the intellectual structure, publication trends, thematic evolution, and emerging research fronts related to AI hallucinations and medical misinformation in healthcare. Data was retrieved from the Scopus database on 25 May 2026 using a predefined search strategy. After applying publication year, subject area, document type, language, and duplicate removal criteria, a final dataset of 1,323 publications published between 2022 and 2025 was analyzed using Bibliometrix/Biblioshiny and VOSviewer software. The findings reveal rapid annual publication growth and increasing global research interest following the emergence of ChatGPT and generative AI technologies. Major research themes included hallucinations, misinformation, clinical decision support, natural language processing, retrieval-augmented generation, explainable AI, and trustworthiness. The United States and China emerged as leading contributors, while digital health and medical informatics journals dominated the publication landscape. The study highlights the growing importance of transparency, reliability, and ethical governance in healthcare AI systems.
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Ammaji Rajitha (2026) studied this question.
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