6 papers
A Synthetic Data-Driven Radiology Foundation Model for Pan-tumor Clinical Diagnosis
Wenhui Lei, Hanyu Chen, Zitian Zhang +13
AI-assisted imaging made substantial advances in tumor diagnosis and management. However, a major barrier to developing robust oncology foundation models is the scarcity of large-s…
A Large Model for Non-invasive and Personalized Management of Breast Cancer from Multiparametric MRI
Luyang Luo, Mingxiang Wu, Mei Li +8
Breast Magnetic Resonance Imaging (MRI) demonstrates the highest sensitivity for breast cancer detection among imaging modalities and is standard practice for high-risk women. Inte…
FreeTumor: Large-Scale Generative Tumor Synthesis in Computed Tomography Images for Improving Tumor Recognition
Linshan Wu, Jiaxin Zhuang, Yanning Zhou +12
Tumor is a leading cause of death worldwide, with an estimated 10 million deaths attributed to tumor-related diseases every year. AI-driven tumor recognition unlocks new possibilit…
ReXplain: Translating Radiology into Patient-Friendly Video Reports
Luyang Luo, Jenanan Vairavamurthy, Xiaoman Zhang +7
Radiology reports, designed for efficient communication between medical experts, often remain incomprehensible to patients. This inaccessibility could potentially lead to anxiety,…
A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges
Zifeng Wang, Hanyin Wang, Benjamin Danek +6
The integration of Large Language Models (LLMs) into medical applications has sparked widespread interest across the healthcare industry, from drug discovery and development to cli…
GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration
Sunan He, Yuxiang Nie, Hongmei Wang +21
Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of m…