ReviewPLOS digital health2025
Clinical insights: A comprehensive review of language models in medicine.
Review in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Large language models in healthcare: applications, evaluation frameworks, and governance pathways - a scoping review and multidimensional framework.Frontiers in digital health · 2026Pooled it
- Large Language Models for Clinical Data Extraction in Workplace Injury Rehabilitation: Protocol for a Retrospective Pilot Study of Accuracy, Fairness, and Methodological Considerations in Workers' Compensation Medical Chart Review.JMIR research protocols · 2026Article
- Clinical drug report generation using multi-phase prompt large language models.Scientific reports · 2026Article
- Memorization in large language models in medicine prevalence characteristics and implications.Nature communications · 2026Article
- Benchmarking Large Language Models for Drug Combination Alerts: Achieving Expert-Level Reliability via Knowledge Grounding and Contextual Reasoning.Journal of medicinal chemistry · 2026Article
- Large language models in patient education for brain tumors: opportunities, risks, and ethical considerations.Frontiers in oncology · 2026Review
- CLIN-LLM: A safety-constrained hybrid framework for clinical diagnosis and treatment generation.PloS one · 2026Article
- Leveraging Language Models for Automated Label Generation in Traumatic Brain Injury Radiology Reports.Research square · 2025Article
- Extracting Clinical Guideline Information Using Two Large Language Models: Evaluation Study.Journal of medical Internet research · 2025Article
- The Development Landscape of Large Language Models for Biomedical Applications.Annual review of biomedical data science · 2025Review
- Comparative Evaluation of Large Language and Multimodal Models in Detecting Spinal Stabilization Systems on X-Ray Images.Journal of clinical medicine · 2025Article
- From general to specific: Tailoring large language models for real-world medical communications.Clinical and translational medicine · 2025Article
- Generative multimodal large language models in mental health care: Applications, opportunities, and challenges.PLOS mental health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper explores the advancements and applications of language models in healthcare, focusing on their clinical use cases. It examines the evolution from early encoder-based systems requiring extensive fine-tuning to state-of-the-art large language and multimodal models capable of integrating text and visual data through in-context learning. The analysis emphasizes locally deployable models, which enhance data privacy and operational autonomy, and their applications in tasks such as text generation, classification, information extraction, and conversational systems. The paper also highlights a structured organization of tasks and a tiered ethical approach, providing a valuable resource for researchers and practitioners, while discussing key challenges related to ethics, evaluation, and implementation.
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.