TY - BOOK
T1 - Internet of Things and Machine Learning for Type I and Type II Diabetes
T2 - Use cases
AU - Dash, Sujata
AU - Pani, Subhendu Kumar
AU - Susilo, Willy
AU - Bernard, Bernard Man Yung
AU - Tse, Gary
N1 - Publisher Copyright:
© 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85214779569&partnerID=8YFLogxK
U2 - 10.1016/C2021-0-03583-5
DO - 10.1016/C2021-0-03583-5
M3 - Book
AN - SCOPUS:85214779569
SN - 9780323956932
BT - Internet of Things and Machine Learning for Type I and Type II Diabetes
ER -
