SynthesisJournal of biomedical science2025
Impact of large language model (ChatGPT) in healthcare: an umbrella review and evidence synthesis.
Synthesis in Journal of biomedical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
77 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Accuracy of Large Language Models in Answering Dental Examination Questions: A Systematic Review and Meta-Analysis.International dental journal · 2026Pooled it
- Diagnostic accuracy of large language models for emergency department triage: a systematic review and meta-analysis.BMC emergency medicine · 2026Pooled it
- Effectiveness of ChatGPT and DeepSeek in Urology Medical Education: Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Smartphone Applications in Dermatology With Special Focus on AI: A European-Continent-Based Review.International journal of dermatology · 2026Review
- AI in Neurological Health Care: Qualitative Study of Patient and Public Perceptions.Journal of medical Internet research · 2026Article
- Commercial large language models for oral cavity cancer staging using descriptive pre-treatment MRI reports: ready for standalone use in clinical practice?Insights into imaging · 2026Article
- Large Language Models for Heterogeneous Data Mining in Liver Disease: Framework Development and Retrospective Validation Study.Journal of medical Internet research · 2026Article
- Psychometric evaluation of the Spanish-language version of the health information technology usability evaluation scale (Health-ITUES).International journal of medical informatics · 2026Article
- Disclosure is not documentation: an open science framework for documenting generative AI use in scholarly research and publication workflows.Research integrity and peer review · 2026Article
- Evaluating Retrieval-Augmented Large Language Models on Anesthesiology Board-Style Questions: Benchmark Study.JMIR formative research · 2026Article
- Mapping the research landscape of virtual reality and artificial intelligence in medical education evaluation: A bibliometric analysis.Medicine · 2026Article
- Large language models decode narrative pathology reports to define clinically relevant subtypes in IgA nephropathy.Nature communications · 2026Article
- Impact of guideline-based prompting on the large language model performance in dental trauma management clinical decision-making.Odontology · 2026Article
- Artificial Intelligence and our journal, "Einstein São Paulo".Einstein (Sao Paulo, Brazil) · 2026Article
- Review
- Advantages, limitations, and ethical concerns of AI-assisted qualitative research in nursing: insights from a human-AI comparative thematic analysis.BMC nursing · 2026Article
- Understanding of Preeclampsia Risk Factors in Large Language Models Compared with a Validated Competing-Risks Model.Diagnostics (Basel, Switzerland) · 2026Article
- Can ChatGPT Be Trusted for Urologic Patient Education? A Comparative Study of Stress Urinary Incontinence-Related Information From Versions 3.5 and 4.International urogynecology journal · 2026Article
- Article
- A Multi-Agent Framework for Real-Time Sentiment Monitoring and Predictive Analysis of Public Health Policies.China CDC weekly · 2026Article
17 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe emergence of Artificial Intelligence (AI), particularly Chat Generative Pre-Trained Transformer (ChatGPT), a Large Language Model (LLM), in healthcare promises to reshape patient care, clinical decision-making, and medical education. This review aims to synthesise research findings to consolidate the implications of ChatGPT integration in healthcare and identify research gaps. MAIN BODY: The umbrella review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Cochrane Library, PubMed, Scopus, Web of Science, and Google Scholar were searched from inception until February 2024. Due to the heterogeneity of the included studies, no quantitative analysis was performed. Instead, information was extracted, summarised, synthesised, and presented in a narrative form. Two reviewers undertook title, abstract, and full text screening independently. The methodological quality and overall rating of the included reviews were assessed using the A Measurement Tool to Assess systematic Reviews (AMSTAR-2) checklist. The review examined 17 studies, comprising 15 systematic reviews and 2 meta-analyses, on ChatGPT in healthcare, revealing diverse focuses. The AMSTAR-2 assessment identified 5 moderate and 12 low-quality reviews, with deficiencies like study design justification and funding source reporting. The most reported theme that emerged was ChatGPT's use in disease diagnosis or clinical decision-making. While 82.4% of studies focused on its general usage, 17.6% explored unique topics like its role in medical examinations and conducting systematic reviews. Among these, 52.9% targeted general healthcare, with 41.2% focusing on specific domains like radiology, neurosurgery, gastroenterology, public health dentistry, and ophthalmology. ChatGPT's use for manuscript review or writing was mentioned in 17.6% of reviews. Promising applications include enhancing patient care and clinical decision-making, though ethical, legal, and accuracy concerns require cautious integration.
conclusionWe summarise the identified areas in reviews regarding ChatGPT's transformative impact in healthcare, highlighting patient care, decision-making, and medical education. Emphasising the importance of ethical regulations and the involvement of policymakers, we urge further investigation to ensure the reliability of ChatGPT and to promote trust in healthcare and research.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.