Mathematical and Computational Oncology

This book constitutes the refereed proceedings of the Third International Symposium on Mathematical and Computational Oncology, ISMCO 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 3 full papers and 4 short papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; spatio-temporal tumor modeling and simulation; general cancer computational biology; mathematical modeling for cancer research; computational methods for anticancer drug development.

Inhalt
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.