| Autor: |
Yakub Sebastian, Xun Ting Tiong, Raman, Valliappan, Alan Yean Yip Fong, Patrick Hang Hui Then |
| Předmět: |
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| Zdroj: |
International Journal of Design, Analysis & Tools for Integrated Circuits & Systems; Oct2017, Vol. 6 Issue 1, p32-37, 6p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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