The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Artificial Intelligence Approaches in Diabetic Prediction
Abstract
Healthcare applications in monitoring and managing diseases have undergone rapid development in medical sectors and play an important in observing and controlling diabetes mellitus (DM). DM is a chronic infection that is caused by extreme blood sugar level. The rapid increase of DM world-wide have the effect of gaining attention to predict DM at early stage. Consequently, various technologies have been used to diagnose diabetes at an early stage to avoid major health defects. The most satisfaction in disease prediction and classification methods has been achieved through AI techniques and algorithms in healthcare. The main of the objective of the study is to provide a detail review on DM, the increase of DM around world-wide, datasets used in diabetic prediction, advance techniques and methods applied for disease prediction, and applications and its limitations used in diabetic prediction. The study also provides a detailed review on recent techniques and methods used in disease prediction, which guides the evolution of AI techniques and will provide a well-grounded knowledge of existing methods.
Related Content
|
Mohammed Adi Al Battashi, Mohamad A. M. Adnan, Asyraf Isyraqi Bin Jamil, Majid Adi Al-Battashi.
© 2026.
30 pages.
|
|
Potchong M. Jackaria, Al-adzran G. Sali, Hana An L. Alvarado, Rashidin H. Moh. Jiripa, Al-sabrie Y. Sahijuan.
© 2026.
26 pages.
|
|
Elizabeth Gross.
© 2026.
30 pages.
|
|
Siti Nazleen Abdul Rabu, Xie Fengli, Ng Man Yi.
© 2026.
44 pages.
|
|
Mohammed Abdul Wajeed.
© 2026.
30 pages.
|
|
Aldammien A. Sukarno, Al-adzkhan N. Abdulbarie, Wati Sheena M. Bulkia, Potchong M. Jackaria.
© 2026.
24 pages.
|
|
Abdulla Sultan Binhareb Almheiri, Humaid Albastaki, Hanadi Alrashdan.
© 2026.
26 pages.
|
|
|