
Mathematical and Computational Oncology
Third International Symposium, ISMCO 2021, Virtual Event, October 11-13, 2021, Proceedings
Springer (Publisher)
Published on 12. December 2021
Book
Paperback/Softback
XXI, 79 pages
978-3-030-91240-6 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
2 s/w Abbildungen, 31 farbige Abbildungen
XXI, 79 p. 33 illus., 31 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 7 mm
Weight
172 gr
ISBN-13
978-3-030-91240-6 (9783030912406)
DOI
10.1007/978-3-030-91241-3
Schweitzer Classification
Other editions
Additional editions

George Bebis | Terry Gaasterland | Mamoru Kato
Mathematical and Computational Oncology
Third International Symposium, ISMCO 2021, Virtual Event, October 11-13, 2021, Proceedings
E-Book
12/2021
Springer
€58.84
Available for download
Persons
Content
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.