7 citations · 10 across the 3 of their papers we have counts for
3 papers
Lymph Node Graph Neural Networks for Cancer Metastasis Prediction
Michal Kazmierski, Benjamin Haibe-Kains
Predicting outcomes, such as survival or metastasis for individual cancer patients is a crucial component of precision oncology. Machine learning (ML) offers a promising way to exp…
A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Data
Michal Kazmierski, Mattea Welch, Sejin Kim +12
Accurate prognosis for an individual patient is a key component of precision oncology. Recent advances in machine learning have enabled the development of models using a wider rang…
Deep-CR MTLR: a Multi-Modal Approach for Cancer Survival Prediction with Competing Risks
Sejin Kim, Michal Kazmierski, Benjamin Haibe-Kains
Accurate survival prediction is crucial for development of precision cancer medicine, creating the need for new sources of prognostic information. Recently, there has been signific…