Research
* denotes equal contribution, and
† denotes corresponding author.
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RaTEScore: A Metric for Radiology Report Generation
Weike Zhao,
Chaoyi Wu,
Xiaoman Zhang,
Ya Zhang,
Yanfeng Wang† ,
Weidi Xie†
EMNLP 2024 main paper
RaTEScore is a novel, entity-aware metric to assess the quality of medical reports generated by AI models.
It emphasizes crucial medical entities such as diagnostic outcomes and anatomical details,
and is robust against complex medical synonyms and sensitive to negation expressions.
The evaluations demonstrate that RaTEScore aligns more closely with human preference than existing metrics.
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Large-scale Long-tailed Disease Diagnosis on Radiology Images
Qiaoyu Zheng*,
Weike Zhao*,
Chaoyi Wu*,
Xiaoman Zhang,
Ya Zhang,
Yanfeng Wang† ,
Weidi Xie†
Nature Communication 2024 (Accept in principle)
In this paper, We build up an academically accessible, large-scale diagnostic dataset that encompasses 5568 disorders linked with 930 unique ICD-10-CM codes,
containing 39,026 cases (192,675 scans). Also, We present a novel architecture that enables to process arbitrary number of input scans, from various imaging
modalities and initialize a new benchmark for multi-modal multi-anatomy long-tailed diagnosis.
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Can GPT-4V(ision) Serve Medical Applications ? Case Studies on GPT-4V for Multimodal Medical Diagnosis
Chaoyi Wu*,
Jiayu Lei*,
Qiaoyu Zheng*,
Weike Zhao*,
Weixiongt Lin*,
Xiaoman Zhang*,
Xiao Zhou*,
Ziheng Zhao*,
Ya Zhang,
Yanfeng Wang ,
Weidi Xie†
Technical Report, 2023.
In this report, we evaluate GPT-4V for multimodal medical diagnosis at case studies, covering 17 human body systems, across 8 clinical imaging modalities. As the cases shown, GPT-4V is still far from clinical usage.
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