2 citations · 4 across the 5 of their papers we have counts for
5 papers
RESPClinBench: Benchmarking Multimodal Clinical Decision-Making and Longitudinal Disease Management in Respiratory Specialty Care
Mouxiao Bian, Zhi Chen, Ruiyao Chen +8
Background: Respiratory specialty care requires multimodal interpretation, longitudinal risk assessment, guideline-concordant intervention, and whole-course management, which are p…
CardioBench: A Real-World Data Benchmark for Evaluating Large Language Models in Clinically Authentic Cardiovascular Care Scenarios
Xiao Li, Mouxiao Bian, Zhaodi Wu +8
Background: Most medical large language model (LLM) benchmarks focus on examination knowledge or isolated tasks and may not reflect the longitudinal, multimodal, and safety-critica…
MedBench v5: A Dynamic, Process-Oriented, and Hallucination-Aware Benchmark for Clinical Multimodal Models
Jinru Ding, Chuchu Jiang, Lu Lu +12
Existing medical AI benchmarks lack process visibility, atomic skill evaluation, and integrated hallucination detection. We introduce MedBench v5, a redesigned benchmark for clinic…
LLM-Mini-CEX: Automatic Evaluation of Large Language Model for Diagnostic Conversation
Xiaoming Shi, Jie Xu, Jinru Ding +9
There is an increasing interest in developing LLMs for medical diagnosis to improve diagnosis efficiency. Despite their alluring technological potential, there is no unified and co…
MedGPTEval: A Dataset and Benchmark to Evaluate Responses of Large Language Models in Medicine
Jie Xu, Lu Lu, Sen Yang +10
METHODS: First, a set of evaluation criteria is designed based on a comprehensive literature review. Second, existing candidate criteria are optimized for using a Delphi method by…