Mathematical and Computational Oncology : Third International Symposium, ISMCO 2021, Virtual Event, October 11–13, 2021, Proceedings / / edited by George Bebis, Terry Gaasterland, Mamoru Kato, Mohammad Kohandel, Kathleen Wilkie

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
• Edizione: 1st ed. 2021.
• Descrizione fisica: 1 online resource (91 pages)
• Disciplina: 572.80285
• Soggetto topico: Computer vision; Computer engineering; Computer networks; Computer Vision; Computer Engineering and Networks
• Persona (resp. second.): BebisGeorge
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Mathematical and computational oncology
• ISBN: 3-030-91241-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910513590203321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Bioinformatics, . 2366-6331 ; ; 13060