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024 7 _a10.1007/978-3-030-91241-3
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245 1 0 _aMathematical and Computational Oncology
_h[electronic resource] :
_bThird International Symposium, ISMCO 2021, Virtual Event, October 11–13, 2021, Proceedings /
_cedited by George Bebis, Terry Gaasterland, Mamoru Kato, Mohammad Kohandel, Kathleen Wilkie.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXXI, 79 p. 33 illus., 31 illus. in color.
_bonline resource.
336 _atext
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337 _acomputer
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338 _aonline resource
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347 _atext file
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490 1 _aLecture Notes in Bioinformatics,
_x2366-6331 ;
_v13060
505 0 _aStatistical 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.
520 _aThis 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.
650 0 _aComputer vision.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 1 4 _aComputer Vision.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aComputer Engineering and Networks.
700 1 _aBebis, George.
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700 1 _aGaasterland, Terry.
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700 1 _aKato, Mamoru.
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700 1 _aKohandel, Mohammad.
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700 1 _aWilkie, Kathleen.
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aLecture Notes in Bioinformatics,
_x2366-6331 ;
_v13060
856 4 0 _uhttps://doi.org/10.1007/978-3-030-91241-3
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