Полное описание

Lu, Zhongyu Machine learning in cancer research with applications in colon cancer and big data analysis / Zhongyu Joan Lu and Qiang Xu, Murad Al-Rajab, Lamogha Chiazor. - Hershey, PA : IGI Global, Medical Information Science Reference. - 19 p. : ill. - URL: https://cat.gpntb.ru/?id=FT/ShowFT&sid=2e2bf605b826f23e83a490aad26451e4. - Includes bibliographical references and index. - ISBN 179987317X. - ISBN 9781799873174. - DOI 10.4018/978-1-7998-7316-7. - Текст : электронный.
"Premier reference source"--Cover.
Содержание:
Chapter 1. Importance of information working with colon cancer research -- Chapter 2. An overview on bioinformatics -- Chapter 3. Research approach with machine learning underpinned -- Chapter 4. Design and procedures for the investigation conducted -- Chapter 5. Findings for the conducted investigations -- Chapter 6. Analysis, discussion, and evaluations for the case studies -- Chapter 7. Final remarks for the research with advanced machine learning methods in colon cancer analysis -- Chapter 8. Importance of research into big data with machine learning approach -- Chapter 9. Overview of big data with machine learning approach -- Chapter 10. Methodology for the research conducted -- Chapter 11. Hybrid-automl system development -- Chapter 12. Research output for the hybrid-automl system -- Chapter 13. Final remarks and further work for the hybrid-automl system.
Рубрики:
Cancer -- Research
Colon (Anatomy) -- Cancer -- Research
Cancer -- Diagnosis
Bioinformatics
Big data
Problem solving -- Data processing
Big data
Bioinformatics
Cancer -- Diagnosis
Cancer -- Research
Colon (Anatomy) -- Cancer -- Research
Problem solving -- Data processing

Аннотация: This book presents a general picture for the latest research output and the state of the art technology in the bioinformatics in cancer research, and big data, machine learning theory and technologies in the various applications.
Доп. точки доступа:
Xu, Q.
Al-Rajab, M.
Chiazor, L.

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Полнотекстовая коллекция книг EBSCO eBooks (Шифр в БД-источнике (EBSKO): on1196821690)

Шифр в сводном ЭК: 378d116279bbee73700ae759b5231db1

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