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Mathematical and Computational Oncology

  • Kartonierter Einband
  • 79 Seiten
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This book constitutes the refereed proceedings of the Third International Symposium on Mathematical and Computational Oncology, IS... Weiterlesen
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Beschreibung

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.

Produktinformationen

Titel: Mathematical and Computational Oncology
Untertitel: Third International Symposium, ISMCO 2021, Virtual Event, October 11-13, 2021, Proceedings
Editor:
EAN: 9783030912406
ISBN: 978-3-030-91240-6
Format: Kartonierter Einband
Herausgeber: Springer, Berlin
Genre: Informatik
Anzahl Seiten: 79
Gewicht: 174g
Größe: H235mm x B5mm x T155mm
Jahr: 2021
Untertitel: Englisch
Auflage: 1st ed. 2021

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