Predictive Analytics For Prevention
Predictive Analytics for Prevention is a computational methodology within preventive care informatics that employs statistical models and machine learning techniques to identify individuals at risk of developing specific diseases before clinical onset, enabling early intervention through data-driven risk stratification and personalized prevention strategies.
89
Publications
5.2K
Citations
661
Authors
245
Institutions
Publications per year
2017–2026
64
Parents
89
Can machine-learning improve cardiovascular risk prediction using routine clinical data?
Stephen Weng, Jenna Reps, Joe Kai et al. · PLoS ONE · 2017 · 1.3K citations · Full text
1–5 of 89
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Indian Institute of Space Science and Technology, India
1 publications · 21 citations
1
h-index
1–5 of 661
245
University of Michigan
Ann Arbor, United States
3 h-index
9 publications
297 citations
University of Bonn
Bonn, Germany
3 h-index
9 publications
434 citations

Cornell University
Ithaca, United States
3 h-index
7 publications
729 citations
The University of Tokyo
Tokyo, Japan
3 h-index
11 publications
243 citations
Duke University
Durham, United States
3 h-index
4 publications
113 citations
University of Technology Sydney
Sydney, Australia
2 h-index
4 publications
1K citations
VA Ann Arbor Healthcare System
Ann Arbor, United States
2 h-index
6 publications
132 citations

Zhejiang University
Hangzhou, China
2 h-index
5 publications
358 citations
1–8 of 245
4 publications · 119 citations
4
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2 publications · 61 citations
2
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2 publications · 46 citations
2
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2 publications · 1.5K citations
2
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2 publications · 359 citations
2
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1–5