Advances in Diabetes Analytics from Clinical and Machine Learning Perspectives

Yakub Sebastian, Xun Ting Tiong, Valliappan Raman, Alan Yean Yip Fong, Patrick Hang Hui Then

Research output: Contribution to journalArticle

Abstract

Diabetes mellitus is among the most prevalent chronic diseases affecting the world’s population today. With the increasing costs associated with diabetes treatments and management, finding the effective early diabetes detection and
screening tools or methods has become the overarching goal for most contemporary diabetes research. Machine learning methods offer a new approach to diabetes analytics that is well-suited to today’s Big Data requirements. They could overcome many constraints inherent in many traditional statistical modeling approaches. In this paper, we offer concise yet detailed discussions on the current progress in diabetes analytics. We also point to several promising research directions in this area.
Original languageEnglish
Pages (from-to)32-37
Number of pages6
JournalInternational Journal of Design, Analysis and Tools for Integrated Circuits and Systems
Volume6
Issue number1
Publication statusPublished - Oct 2017
Externally publishedYes

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