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Computational Mathematics Modeling in Cancer Analysis - First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings (Paperback, 1st ed. 2022) Loot Price: R1,376
Discovery Miles 13 760
Computational Mathematics Modeling in Cancer Analysis - First International Workshop, CMMCA 2022, Held in Conjunction with...

Computational Mathematics Modeling in Cancer Analysis - First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings (Paperback, 1st ed. 2022)

Wenjian Qin, Nazar Zaki, Fa Zhang, Jia Wu, Fan Yang

Series: Lecture Notes in Computer Science, 13574

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Loot Price R1,376 Discovery Miles 13 760 | Repayment Terms: R129 pm x 12*

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This book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Lecture Notes in Computer Science, 13574
Release date: September 2022
First published: 2022
Editors: Wenjian Qin • Nazar Zaki • Fa Zhang • Jia Wu • Fan Yang
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 160
Edition: 1st ed. 2022
ISBN-13: 978-3-03-117265-6
Categories: Books > Computing & IT > General theory of computing > General
Books > Computing & IT > Computer communications & networking > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
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LSN: 3-03-117265-5
Barcode: 9783031172656

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