390 citations · 390 across the 2 of their papers we have counts for
2 papers
eess.IV2024
Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium
Haris Shuaib, Gareth J Barker, Peter Sasieni +16
Objective: To report imaging protocol and scheduling variance in routine care of glioblastoma patients in order to demonstrate challenges of integrating deep-learning models in gli…
cs.LG2022★ 390 cited
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…