Predictive Risk Scoring
Predictive Risk Scoring is a computational methodology within predictive analytics that quantifies an individual's likelihood of experiencing adverse health outcomes through the integration of demographic, clinical, and behavioral data to stratify population-level risk.
500
Publications
29.2K
Citations
4.8K
Authors
1.4K
Institutions
Publications per year
2017–2026
289
500
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
The accuracy, fairness, and limits of predicting recidivism
Julia Dressel, Hany Farid · Science Advances · 2018 · 1K citations · Full text
Predicting the 30-Year Risk of Cardiovascular Disease
Michael Pencina, Ralph B. D’Agostino, Martin G. Larson et al. · Circulation · 2009 · 861 citations · Full text
Public Health, Preventive Medicine, Epidemiologic Methods +16
1–5 of 500
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1.4K
Harvard University
Cambridge, United States
18 h-index
141 publications
56.3K citations

Brigham and Women's Hospital
Boston, United States
15 h-index
59 publications
17.3K citations
Massachusetts General Hospital
Boston, United States
12 h-index
50 publications
10.7K citations
University of Oxford
Oxford, United Kingdom
12 h-index
34 publications
1.3K citations
Inserm
Paris, France
11 h-index
44 publications
4.5K citations

Imperial College London
London, United Kingdom
10 h-index
20 publications
5.2K citations

The University of Melbourne
Melbourne, Australia
10 h-index
16 publications
3.8K citations
University of Cambridge
Cambridge, United Kingdom
10 h-index
34 publications
2K citations
1–8 of 1.4K
24 publications · 2.4K citations
20
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19 publications · 598 citations
14
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Repository · 16 publications · 350 citations
11
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6 publications · 760 citations
6
h-index
WJG · 5 publications · 205 citations
5
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1–5