Diagnostic Uncertainty Quantification is a formal methodological framework within diagnostic systems engineering that characterizes the degree of confidence in diagnostic outcomes by systematically assessing and quantifying uncertainties arising from sensor noise, model inaccuracies, and operational variability across actuator, sensor, flow assurance, and decision support contexts.
172
Publications
10.1K
Citations
952
Authors
435
Institutions
Publications per year
2017–2026
66
Publications
172
1–5 of 172
Authors
952
- RA
3
h-index
- AK
3
h-index
- SN
3
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- EF
2
h-index
- BA
2
h-index
1–5 of 952
Institutions
435
Harvard University
Cambridge, United States
6 h-index
10 publications
833 citations
University of Michigan
Ann Arbor, United States
5 h-index
10 publications
885 citations
University of Birmingham
Birmingham, United Kingdom
5 h-index
14 publications
560 citations
Massachusetts General Hospital
Boston, United States
5 h-index
19 publications
2.1K citations
University of Washington
Seattle, United States
4 h-index
17 publications
735 citations
University of Oxford
Oxford, United Kingdom
4 h-index
4 publications
142 citations
University of Pittsburgh
Pittsburgh, United States
4 h-index
14 publications
423 citations
National University of Singapore
Singapore, Singapore
3 h-index
3 publications
156 citations
1–8 of 435
Venues
- PubMed
Repository · 8 publications · 394 citations
8
h-index
- Journal of Evaluation in Clinical Practice
3 publications · 114 citations
3
h-index
- Archives of Internal Medicine
3 publications · 179 citations
3
h-index
- Clinical Chemistry and Laboratory Medicine (CCLM)
3 publications · 200 citations
3
h-index
- New England Journal of Medicine
NEJM · 3 publications · 1K citations
3
h-index
1–5