Mathematical and Computational Oncology

Statistical and Machine Learning Methods for Cancer Research Image Classification of Skin Cancer: Using Deep Learning as a Tool for Skin Self-Examinations.- Predictive Signatures for Lung Adenocarcinoma Prognostic Trajectory by Omics Data Integration and Ensemble Learning.- The Role of Hydrophobicity in Peptide-MHC Binding.- Spatio-temporal tumor modeling and simulation Simulating cytotoxic T-lymphocyte & cancer cells interactions : An LSTM-based approach to surrogate an agent-based model.- General cancer computational biology Strategies to reduce long-term drug resistance by considering effects of differential selective treatments.- Mathematical Modeling for Cancer Research Improved Geometric Configuration for the Bladder Cancer BCG-based Immunotherapy Treatment Model.- Computational methods for anticancer drug development Run for your life – an integrated virtual tissue platform for incorporating exercise oncology into immunotherapy.