Internet of Things and machine learning for type I and type II diabetes : use cases /
Provides a medium of exchange of expertise and addresses the concerns, needs, and problems associated with Type I and Type II diabetes. Expert contributions come from researchers across biomedical, data mining, and deep learning. This is an essential resource for both the AI and Biomedical research...
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| Andre forfattere: | , , , , |
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| Format: | eBog |
| Sprog: | engelsk |
| Udgivet: |
London ; San Diego, CA :
Academic Press,
[2024]
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| Fag: | |
| Online adgang: | ScienceDirect |
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| Summary: | Provides a medium of exchange of expertise and addresses the concerns, needs, and problems associated with Type I and Type II diabetes. Expert contributions come from researchers across biomedical, data mining, and deep learning. This is an essential resource for both the AI and Biomedical research community, crossing various sectors for broad coverage of the concepts, themes, and instrumentalities of this important and evolving area. Coverage includes IoT, AI, Deep Learning, Machine Learning and Big Data Analytics for diabetes and health informatics. |
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| Fysisk beskrivelse: | 1 online resource |
| Bibliografi: | Includes bibliographical references and index. |
| ISBN: | 9780323956932 0323956939 |