ReviewBioengineering (Basel, Switzerland)2025
Large Language Models in Healthcare and Medical Applications: A Review.
Review in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 1 of them a synthesis 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
85 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Use of large language models for providing automated feedback in medical imaging education: a systematic review.Frontiers in medicine · 2026Pooled it
- A Patient Simulation Framework for Risk Assessment of Conversational Health Care AI: Development and Evaluation Study.JMIR AI · 2026Article
- Large language models' performance in answering common patient questions about colonoscopy: an expert-based evaluation.BMC gastroenterology · 2026Observational
- Pediatric social robotics in ASD: navigating AI blind-spots toward clinical validation.European journal of pediatrics · 2026Review
- A Clinician-Centered Evaluation Framework for Large Language Models in Patient Education: Integrating the Technology Acceptance Model and Medical Condition Regard Scale.JMIR formative research · 2026Article
- Large language models for tympanostomy patient education: readability and guideline adherence.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- CPS-Net (Collaborating Physicians in Silico Network): A Decentralized Multi-Agent Transformer Framework for Specialty-Aware Disease Prediction.Journal of medical systems · 2026Article
- Large language models answering structured questions on external cervical resorption: a comparative study.Odontology · 2026Article
- Large Language Models for Heterogeneous Data Mining in Liver Disease: Framework Development and Retrospective Validation Study.Journal of medical Internet research · 2026Article
- Community pharmacists' knowledge, attitudes, and practices toward self-medication for common cold and influenza: A COM-B model-based cross-sectional study.Exploratory research in clinical and social pharmacy · 2026Article
- The Reliability of Human Evaluation of Large Language Models in Health Care Settings: Scoping Review.Journal of medical Internet research · 2026Article
- Methods of Evaluating Large Language Model-Based Health Care Applications Used by Nonprofessionals: Protocol for a Scoping Review.JMIR research protocols · 2026Article
- Nurse-Led Large Language Model Chatbot for Predicting and Preventing Complications After Coronary Artery Bypass Grafting: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2026Article
- Use of Large Language Models to Enhance Failure Mode and Effects Analysis: A Case Study.Advances in radiation oncology · 2026Article
- Performance evaluation of large language models in real-world perinatal medication consultations: a cross-sectional study.International journal of clinical pharmacy · 2026Article
- A Hybrid Rule-Based and Large Language Model Artificial Intelligence System for Electrodiagnostic Reporting: Two-Center Retrospective Evaluation.Muscle & nerve · 2026Observational
- LLM-Mediated Smart Tele-Primary Care for Rural Older Adults: A Caregiver-Centered and Scenario-Assessed Framework for Respiratory Infection Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Large Language Models for Postoperative Decision Support: Comparative Analysis.Journal of medical Internet research · 2026Article
- Diagnostic Performance and Workup Efficiency of Large Language Models in Secondary Hypertension: A Blinded Comparative Study.Diagnostics (Basel, Switzerland) · 2026Article
- LLM-powered prostate cancer staging from PSMA-PET/CT reports using PROMISE v2.European journal of nuclear medicine and molecular imaging · 2026Article
25 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper provides a systematic and in-depth examination of large language models (LLMs) in the healthcare domain, addressing their significant potential to transform medical practice through advanced natural language processing capabilities. Current implementations demonstrate LLMs' promising applications across clinical decision support, medical education, diagnostics, and patient care, while highlighting critical challenges in privacy, ethical deployment, and factual accuracy that require resolution for responsible integration into healthcare systems. This paper provides a comprehensive understanding of the background of healthcare LLMs, the evolution and architectural foundation, and the multimodal capabilities. Key methodological aspects-such as domain-specific data acquisition, large-scale pre-training, supervised fine-tuning, prompt engineering, and in-context learning-are explored in the context of healthcare use cases. The paper highlights the trends and categorizes prominent application areas in medicine. Additionally, it critically examines the prevailing technical and social challenges of healthcare LLMs, including issues of model bias, interpretability, ethics, governance, fairness, equity, data privacy, and regulatory compliance. The survey concludes with an outlook on emerging research directions and strategic recommendations for the development and deployment of healthcare LLMs.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.