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Big data analytics for healthcare : datasets, techniques, life cycles, management, and applications / edited by Pantea Keikhosrokiani.
- Format:
- Book
- Language:
- English
- Subjects (All):
- Medical care--Data processing.
- Medical care.
- Medicine--Data processing.
- Medicine.
- Big data.
- Data mining.
- Genre:
- Electronic books.
- Physical Description:
- 1 online resource (xx, 334 pages) : illustrations (some color)
- Place of Publication:
- London ; San Diego, CA : Academic Press, [2022]
- Summary:
- Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work.
- Notes:
- Includes bibliographical references and index.
- Description based on online resource; title from digital title page (viewed on June 22, 2022).
- Other Format:
- Print version:
- ISBN:
- 9780323985161
- 0323985165
- 9780323919074
- 0323919073
- OCLC:
- 1319344778
- Access Restriction:
- Restricted for use by site license.
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