Predictive Model Performance
Predictive Model Performance is a quantitative assessment metric that evaluates the accuracy, reliability, and generalizability of a predictive model in forecasting frailty outcomes based on predefined validation criteria and clinical relevance.
7K
Publications
440.5K
Citations
33.9K
Authors
6.8K
Institutions
Publications per year
2017–2026
5K
Parents
7K
A working guide to boosted regression trees
Jane Elith, John R. Leathwick, Trevor Hastie · Journal of Animal Ecology · 2008 · 6.5K citations · Full text
Computing, Biostatistics, Ecology +14
1–5 of 7K
33.9K
31
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18
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15
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15
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14
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1–5 of 33.9K
6.8K
Harvard University
Cambridge, United States
54 h-index
491 publications
40.3K citations
University College London
London, United Kingdom
43 h-index
297 publications
48.7K citations
University of Cambridge
Cambridge, United Kingdom
42 h-index
196 publications
15.3K citations
University of Washington
Seattle, United States
40 h-index
188 publications
20.6K citations
Stanford University
Stanford, United States
35 h-index
254 publications
24.2K citations
University of Oxford
Oxford, United Kingdom
35 h-index
183 publications
25.3K citations
Duke University
Durham, United States
35 h-index
151 publications
19.9K citations
Massachusetts General Hospital
Boston, United States
35 h-index
257 publications
31.2K citations
1–8 of 6.8K
187 publications · 9.7K citations
52
h-index
166 publications · 8.1K citations
51
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61 publications · 7K citations
37
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Repository · 120 publications · 6.5K citations
36
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46 publications · 7K citations
33
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