ReviewThe Japanese dental science review2026
The role of large language models in dental diagnosis, decision-making, and communication: A systematic review.
Review in The Japanese dental science review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed.
- Impact of guideline-based prompting on the large language model performance in dental trauma management clinical decision-making.Odontology · 2026Article
- Do large language models differ in their pharmacology-related response quality for oral and maxillofacial surgery? a blinded expert benchmark study.BMC oral health · 2026Article
- JADE: jawbone lesion diagnosis and decision supporting system.Dento maxillo facial radiology · 2026Article
- Prompt sensitivity of large language models in orthodontic patient counseling: a scenario-based experimental study.BMC oral health · 2026Article
- Artificial Intelligence Perceptions and Readiness Among Clinical Nurses: A Latent Profile Analysis With Implications for Nursing Management.Journal of nursing management · 2026Article
- Cross-platform evaluation of LLM-generated educational texts on cardiac myxoma: quality, readability, and actionability using network analysis and latent profile analysis.Frontiers in cardiovascular medicine · 2026Article
- Evaluating large language models for myocardial infarction public health education: a comparative study on information quality, transparency and readability.Frontiers in public health · 2026Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of LLMs in the healthcare sector offers significant potential for improving medical practice and patient care. They assist in medical diagnosis by analyzing patient symptoms and other relevant data. This systematic review proposes to assess the existing literature on the use of LLMs
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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.