ArticleJournal of medical systems2025
Dissecting HealthBench: Disease Spectrum, Clinical Diversity, and Data Insights from Multi-Turn Clinical AI Evaluation Benchmark.
Article in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Comparison of Two AI Chatbots for Diagnosis and Providing Treatment Suggestions in Retinopathy of Prematurity: Retrospective Study.Journal of medical Internet research · 2026Article
- Iterative Multidisciplinary Development and Evaluation of a Patient-Facing Social Determinants of Health Chatbot Using Synthetic Data Simulation: Mixed Methods Study.JMIR formative research · 2026Article
- Evaluating the First CE-Marked LLM-Based Chatbot for Evidence-Based Neurology.European journal of neurology · 2026Article
- Mindbench.ai: an actionable platform to evaluate the profile and performance of large language models in a mental healthcare context.NPP - digital psychiatry and neuroscience · 2025Article
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
HealthBench is an open-source, large-scale benchmark consisting of 5,000 multi-turn clinical conversations evaluated against 48,562 criteria developed by clinicians. Recognized as a significant advancement in assessing realistic artificial intelligence (AI) models, HealthBench deserves further exploration. In this article, we systematically analyze the benchmark's disease spectrum, diagnostic and therapeutic focuses, and demographic diversity. We evaluate its representativeness and strengths, as well as the essential limitations that AI researchers and clinicians should consider when using it for realistic model evaluations.
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.