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Record Nr. |
UNINA9910513590203321 |
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Titolo |
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 |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
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ISBN |
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Edizione |
[1st ed. 2021.] |
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Descrizione fisica |
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1 online resource (91 pages) |
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Collana |
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Lecture Notes in Bioinformatics, , 2366-6331 ; ; 13060 |
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Disciplina |
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Soggetti |
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Computer vision |
Computer engineering |
Computer networks |
Computer Vision |
Computer Engineering and Networks |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the Third |
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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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