Article

Psychometric Alignment Between Human and Artificial Intelligence Performance in Cardiology Residency In-Service Examinations

2026-04-06

Abstract excerpt

<title>Abstract</title> <p>Background Large language models (LLMs) have demonstrated rapidly expanding capabilities across medical knowledge tasks, including professional examinations. However, most existing evaluations focus primarily on overall accuracy and provide limited insight into how AI performance relates to the psychometric structure of examination items. Methods We evaluated the performance of five l...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 0e976b72-e2b8-5b8e-8482-8d5c180c17b1
DOI: 10.21203/rs.3.rs-9247601/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Psychometric Alignment Between Human and Artificial Intelligence Performance in Cardiology Residency In-Service ExaminationsDOI 10.21203/rs.3.rs-9247601/v1Read

Performance of Advanced Large Language Models (GPT-4o, GPT-4, Gemini 1.5 Pro, Claude 3 Opus) on Japanese Medical Licensing Examination: A Comparative StudySemantic proximity Read

Cardiology Knowledge Assessment of Retrieval-Augmented Open versus Proprietary Large Language ModelsSemantic proximity Read

Modern Artificial Intelligence and Large Language Models in Graduate Medical Education: A Scoping Review of Attitudes, Applications & PracticeSemantic proximity Read

Clinical Knowledge and Reasoning Abilities of AI Large Language Models in Anesthesiology: A Comparative Study on the ABA ExamSemantic proximity Read

Psychometric Performance and Student Perceptions of AI- versus Human-Generated Multiple-Choice Questions: The AHEAD Randomized Controlled TrialSemantic proximity Read

Comparison of Large Language Models’ Performance on Neurosurgical Board Examination QuestionsSemantic proximity Read

Comparative Performance of General-Purpose Large Language Models and a Specialized Clinical AI Tool on OKAP-Style Ophthalmology QuestionsSemantic proximity Read

Evaluating Capabilities of Large Language Models: Performance of GPT4 on Surgical Knowledge AssessmentsSemantic proximity Read

QUEST-AI: A System for Question Generation, Verification, and Refinement using AI for USMLE-Style ExamsSemantic proximity Read

Multimodal Large Language Model Passes Specialty Board Examination and Surpasses Human Test-Taker Scores: A Comparative Analysis Examining the Stepwise Impact of Model Prompting Strategies on PerformanceSemantic proximity Read

General purpose large language models match human performance on gastroenterology board exam self-assessmentsSemantic proximity Read

Quality assurance and validity of AI-generated Single Best Answer questionsSemantic proximity Read