Internet of Things and Machine Learning for Type I and Type II Diabetes: Use cases

Sujata Dash; Subhendu Kumar Pani; Willy Susilo; Bernard Man Yung Bernard; Gary Tse

doi:10.1016/C2021-0-03583-5

Internet of Things and Machine Learning for Type I and Type II Diabetes: Use cases

Sujata Dash
, Subhendu Kumar Pani
, Willy Susilo
, Bernard Man Yung Bernard
, Gary Tse

Research output: Book/Report › Book › peer-review

1 Citation (Scopus)

Abstract

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 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.

Original language	English
Number of pages	431
ISBN (Electronic)	9780323956864
DOIs	https://doi.org/10.1016/C2021-0-03583-5
Publication status	Published - 1 Jan 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1016/C2021-0-03583-5

Cite this

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Internet of Things and Machine Learning for Type I and Type II Diabetes: Use cases

Abstract

UN SDGs

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