1 citations · 2 across the 4 of their papers we have counts for
4 papers
Hybrid artificial intelligence echogenic components-based diagnosis of adnexal masses on ultrasound
Roni Yoeli-Bik, Heather M. Whitney, Hui Li +6
Background: Adnexal masses are heterogeneous and have varied sonographic presentations, making them difficult to diagnose correctly. Purpose: Our study aimed to develop an innovati…
AI analysis of medical images at scale as a health disparities probe: a feasibility demonstration using chest radiographs
Heather M. Whitney, Hui Li, Karen Drukker +2
Health disparities (differences in non-genetic conditions that influence health) can be associated with differences in burden of disease by groups within a population. Social deter…
Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx
Trung-Hieu Hoang, Jordan Fuhrman, Ravi Madduri +8
Facilitating large-scale, cross-institutional collaboration in biomedical machine learning projects requires a trustworthy and resilient federated learning (FL) environment to ensu…
APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service
Zilinghan Li, Shilan He, Pranshu Chaturvedi +9
Cross-silo privacy-preserving federated learning (PPFL) is a powerful tool to collaboratively train robust and generalized machine learning (ML) models without sharing sensitive (e…