ArticleBriefings in bioinformatics2023
Opportunities and challenges for ChatGPT and large language models in biomedicine and health.
Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 188 papers, 3 of them syntheses that pooled it.
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Who cites it
188 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Evaluating Large Language Models in Ophthalmology: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Large Language Models for Chatbot Health Advice Studies: A Systematic Review.JAMA network open · 2025Pooled it
- Performance of ChatGPT Across Different Versions in Medical Licensing Examinations Worldwide: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Katalyst: knowledge-guided semantic alignment via contrastive learning for enzyme turnover prediction.Bioinformatics (Oxford, England) · 2026Article
- A framework for extraction of clinical information from radiological mammography reports using large language models and retrieval augmented generation.BMC medical informatics and decision making · 2026Article
- Lung cancer research: how natural language processing enhances clinical data extraction.Journal of thoracic disease · 2026Article
- Agentic genomics: From pipeline automation to autonomous validation.Cell genomics · 2026Review
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- Comparison of proprietary and fine-tuned large language models for multi-label classification of billing codes from radiology reports.European radiology · 2026Article
- A Large Language Model-Driven System for Advance Care Planning Training Among Health Care Providers in the Chinese Context: Development and Technical Evaluation.Journal of medical Internet research · 2026Article
- Performance of Large Language Models for Oncology Nursing Decision Support: Cross-Sectional Study.Journal of medical Internet research · 2026Article
- Tutorial: guidance on the use of large language models for medical research.Nature protocols · 2026Review
- Article
- LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology.ACM transactions on computing for healthcare · 2026Article
- Memorization in large language models in medicine prevalence characteristics and implications.Nature communications · 2026Article
- Performance of GPT-based large language models in hepatocellular carcinoma stratification: liver function assessment, BCLC staging, and treatment recommendations.Scientific reports · 2026Article
- Statistical Consistency in Artificial Intelligence-Assisted Computations: A Comparison of SPSS 31.0 and GPT-5.5.Cureus · 2026Article
- Consistency in causal reasoning for large language models in scenarios of HIV antiretroviral treatment, drug interactions, and side effects.NPJ digital medicine · 2026Article
- iS2C2: a cointelligent platform for mechanistic discovery of disease cellular crosstalk.Signal transduction and targeted therapy · 2026Article
- Cell-o1 : training LLMs to solve single-cell reasoning puzzles with reinforcement learning.Bioinformatics (Oxford, England) · 2026Article
128 more citing papers are in PubMed but not listed here.
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Authors and funding
14 authors.
Funding
Abstract
ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and health. In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health. Specifically, we explore the areas of biomedical information retrieval, question answering, medical text summarization, information extraction and medical education and investigate whether LLMs possess the transformative power to revolutionize these tasks or whether the distinct complexities of biomedical domain presents unique challenges. Following an extensive literature survey, we find that significant advances have been made in the field of text generation tasks, surpassing the previous state-of-the-art methods. For other applications, the advances have been modest. Overall, LLMs have not yet revolutionized biomedicine, but recent rapid progress indicates that such methods hold great potential to provide valuable means for accelerating discovery and improving health. We also find that the use of LLMs, like ChatGPT, in the fields of biomedicine and health entails various risks and challenges, including fabricated information in its generated responses, as well as legal and privacy concerns associated with sensitive patient data. We believe this survey can provide a comprehensive and timely overview to biomedical researchers and healthcare practitioners on the opportunities and challenges associated with using ChatGPT and other LLMs for transforming biomedicine and health.
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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 OpenQuestion graph.