Probabilistic Diagnostic Modeling
Probabilistic Diagnostic Modeling is a computational framework within diagnostic decision support that employs probabilistic reasoning to represent and infer the likelihood of diseases given observed symptoms, thereby distinguishing itself from deterministic methods by explicitly quantifying uncertainty in diagnostic hypotheses.
434
Publications
23.7K
Citations
1.3K
Authors
540
Institutions
Publications per year
2017–2026
73
Parents
434
Refining clinical diagnosis with likelihood ratios
David A. Grimes, Kenneth F. Schulz · The Lancet · 2005 · 828 citations
1–5 of 434
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University of Pittsburgh Medical Center, United States
6 publications · 177 citations
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1–5 of 1.3K
540
Stanford University
Stanford, United States
13 h-index
50 publications
9.5K citations
University of Michigan
Ann Arbor, United States
9 h-index
12 publications
329 citations
University of Pittsburgh
Pittsburgh, United States
8 h-index
22 publications
1.5K citations
University of California, Irvine
Irvine, United States
8 h-index
12 publications
584 citations
University of Oxford
Oxford, United Kingdom
6 h-index
25 publications
1K citations
Erasmus University Rotterdam
Rotterdam, The Netherlands
6 h-index
17 publications
1.2K citations
University of Wisconsin–Madison
Madison, United States
6 h-index
16 publications
583 citations
Oregon State University
Corvallis, United States
5 h-index
5 publications
285 citations
1–8 of 540
20 publications · 1.1K citations
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Repository · 21 publications · 869 citations
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MDM · 15 publications · 730 citations
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10 publications · 369 citations
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9 publications · 308 citations
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