The authors created 50,401 questions from ICD-10-coded diagnoses for 4,739 UK Biobank participants.
Clinical agents learn to gather evidence across longitudinal MRI records
CASE trains a compact vision-language model to select and synthesize relevant clinical evidence rather than answer from preselected inputs.
Chinese Tech
Minye Shao · Chaohui Yu · Yixuan Wu · Fan Wang · Ling Shao · Yang Long
Durham University · DAMO Academy, Alibaba Group · Hupan Laboratory · University of the Chinese Academy of Sciences
Research Digest··2 min read
Shao and colleagues built an interactive benchmark in which agents must investigate patient records and MRI scans from multiple visits before answering clinical questions.
Why this paper
From University of the Chinese Academy of Sciences and 3 others
In one line
CASE agents achieve over 16% and 10% relative improvements in answer accuracy over GPT-5.4 and Claude Opus 4.8 on longitudinal medical reasoning.
What we could check
- ·No code link found
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- ·No stated limitations found
- ✓Reports numbers on named benchmarks
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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