390 citations · 391 across the 2 of their papers we have counts for
3 papers
The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information
D. Abler, O. Pusterla, A. Joye-Kühnis +19
Background: Radiomics shows promise in characterizing glioblastoma, but its added value over clinical and molecular predictors has yet to be proven. This study assessed the added v…
Modelling the Lymphatic Metastatic Progression Pathways of OPSCC from Multi-Institutional Datasets
Roman Ludwig, Adrian Schubert, Dorothea Barbatei +11
The elective clinical target volume (CTV-N) in oropharyngeal squamous cell carcinoma (OPSCC) is currently based mostly on the prevalence of lymph node metastases in different lymph…
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…