5 citations · 5 across the 1 of their papers we have counts for
4 papers
A Vision-Language Foundation Model for Zero-shot Clinical Collaboration and Automated Concept Discovery in Dermatology
Siyuan Yan, Xieji Li, Dan Mo +28
Medical foundation models have shown promise in controlled benchmarks, yet widespread deployment remains hindered by reliance on task-specific fine-tuning. Here, we introduce DermF…
Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology
Siyuan Yan, Ming Hu, Yiwen Jiang +5
The emergence of vision-language models has transformed medical AI, enabling unprecedented advances in diagnostic capability and clinical applications. However, progress in dermato…
A Multimodal Vision Foundation Model for Clinical Dermatology
Siyuan Yan, Zhen Yu, Clare Primiero +22
Diagnosing and treating skin diseases require advanced visual skills across domains and the ability to synthesize information from multiple imaging modalities. While current deep l…
Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study
Tirtha Chanda, Sarah Haggenmueller, Tabea-Clara Bucher +19
Artificial intelligence (AI) systems have substantially improved dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing clinicians' c…