4 papers
Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration
Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7
Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory hurdles associated with site-spe…
Standardized Methods and Recommendations for Green Federated Learning
Austin Tapp, Holger R. Roth, Ziyue Xu +3
Federated learning (FL) enables collaborative model training over privacy-sensitive, distributed data, but its environmental impact is difficult to compare across studies due to in…
FeTTL: Federated Template and Task Learning for Multi-Institutional Medical Imaging
Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7
Federated learning enables collaborative model training across geographically distributed medical centers while preserving data privacy. However, domain shifts and heterogeneity in…
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions
Hareem Nisar, Syed Muhammad Anwar, Zhifan Jiang +5
Large vision language models (VLMs) have progressed incredibly from research to applicability for general-purpose use cases. LLaVA-Med, a pioneering large language and vision assis…