ArticleJournal of medical Internet research2025
Beyond Benchmarks: Evaluating Generalist Medical Artificial Intelligence With Psychometrics.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- The IMPACT framework for evaluating generative AI in critical care: development and multinational consensus validation.Annals of intensive care · 2026Article
- Beyond Benchmarks: Evaluating Generalist Medical Artificial Intelligence With Psychometrics.Journal of medical Internet research · 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Unlabelled: Rigorous evaluation of generalist medical artificial intelligence (GMAI) is imperative to ensure their utility and safety before implementation in health care. Current evaluation strategies rely heavily on benchmarks, which can suffer from issues with data contamination and cannot explain how GMAI might fail (lacking explanatory power) or in what circumstances (lacking predictive power). To address these limitations, we propose a new methodology to improve the quality of GMAI evaluation using construct-oriented processes. Drawing on modern psychometric techniques, we introduce approaches to construct identification and present alternative assessment formats for different domains of professional skills, knowledge, and behaviors that are essential for safe practice. We also discuss the need for human oversight in future GMAI adoption.
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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.