Mathematical and Computational Oncology (eBook, PDF)

Third International Symposium, ISMCO 2021, Virtual Event, October 11-13, 2021, Proceedings
Redaktion: Bebis, George; Wilkie, Kathleen; Kohandel, Mohammad; Kato, Mamoru; Gaasterland, Terry

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 79
• Erscheinungstermin: 11. Dezember 2021
• Englisch
• ISBN-13: 9783030912413
• Artikelnr.: 63303876

Inhaltsangabe

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.