ArticleNPJ digital medicine2025
Cognitive bias in clinical large language models.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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
16 citing papers in PubMed.
- Development of a Framework for Evaluating Large Language Model Safety and Reliability: a Proof-of-Concept Evaluation.Journal of medical systems · 2026Article
- Sustaining High Reliability Amid Artificial Intelligence Adoption in Oncology.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2026Article
- When AI agrees with us: large language models as amplifiers of scientific bias.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Simulated self-assessment in large language models: A psychometric approach to AI self-efficacy.Computers in human behavior. Artificial humans · 2026Article
- Biases of large language models in diagnosing Cushing's syndrome.World journal of methodology · 2026Review
- Integrating large language models for enhanced predictive analytics in healthcare.NPJ digital medicine · 2026Article
- Lessons learned from viral hepatitis testing that inform law and policy responses to steatotic liver disease.Nature reviews. Gastroenterology & hepatology · 2026Review
- Benchmarking Large Language Models Using a Best Evidence Topic Report in a Patient With Early Non-Small Cell Lung Cancer.Interdisciplinary cardiovascular and thoracic surgery · 2026Article
- Implicit bias in safety-aligned large language models: A multi-faceted evaluation of clinical decision-making and health equity.PloS one · 2026Article
- Bio-Inspired Artificial Intelligence Multimorbidity Score for Human-Machine Clinical Risk Stratification.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Ten years on: how far have we come in patient engagement in diagnosis?Diagnosis (Berlin, Germany) · 2025Review
- Reply to "When do large language models cross the line: "reasoning" red teaming in healthcare".NPJ digital medicine · 2025Article
- The perils of politeness: how large language models may amplify medical misinformation.NPJ digital medicine · 2025Article
- Artificial intelligence for autoimmune diseases.NPJ digital medicine · 2025Article
- Transforming healthcare delivery with conversational AI platforms.NPJ digital medicine · 2025Article
- Large language models for neurology: a mini review.Frontiers in digital 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.