ARTIFICIAL INTELLIGENCE IN DATA-DRIVEN ANALYTICS FOR THE PERSONALIZED HEALTHCARE

被引:0
|
作者
Sivabalaselvamani, D. [1 ]
Selvakarthi, D. [2 ]
Yogapriya, J. [3 ]
Thiruvenkatasuresh, M. P. [4 ]
Maruthappa, Muthukumaran [5 ]
Chandra, Akkaraju Sailesh [6 ]
机构
[1] Kongu Engn Coll, Dept Comp Applicat, Erode 638060, Tamil Nadu, India
[2] Kongu Engn Coll, Dept Elect & Instrumentat Engn, Erode 638060, Tamil Nadu, India
[3] Kongunadu Coll Engn & Technol, Dept Comp Sci & Engn, Trichy, Tamil Nadu, India
[4] Erode Sengunthar Engn Coll, Dept Comp Sci & Engn, Erode, Tamil Nadu, India
[5] Sunway Univ, Sch Engn & Technol, Petaling Jaya, Selangor, Malaysia
[6] Christ Univ Deemed Univ, Inst Management, Bengaluru 560085, Karnataka, India
关键词
smart healthcare; Big Data Analytics; Data-driven medicine; Digital health; Health intelligence; Data-driven analytics; Expert systems;
D O I
10.1109/ICCCI50826.2021.9402703
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Among the various developments in progress over the last decade, we have seen the generous growth of information investigation to take care of, plan, and use a lot of information beneficially. Be that as it may, because the analysis of evidence will only operate for authentic information and have findings as predefined by individuals, explicit principle-based calculations have been developed to broaden the investigation of information, "Which is usually referred to as "AI". AI didn't expect PCs to be personalized unambiguously, which is a definite bit of leeway. In order to break down information and construct complicated equations to foresee models, which was called prescient analysis, AI was then joined with information inquiry. A set of laws characterized by persons, known as prescient equations, drive the prescient inquiry, and are used to break down genuine knowledge in order to predict potential outcomes.
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页数:5
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