Observational Data Modeling
Observational Data Modeling is a methodological framework within clinical data modeling that distinguishes itself by structuring and standardizing data derived from real-world patient observations without active intervention, enabling the systematic representation of naturally occurring clinical phenomena for analysis and inference.
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Publications
33.6K
Citations
1.5K
Authors
756
Institutions
Publications per year
2017–2026
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Harvard University
Cambridge, United States
16 h-index
69 publications
3.2K citations
University of Washington
Seattle, United States
13 h-index
26 publications
1.3K citations

Johns Hopkins University
Baltimore, United States
11 h-index
33 publications
2.3K citations
University of Pennsylvania
Philadelphia, United States
10 h-index
20 publications
1K citations
Carnegie Mellon University
Pittsburgh, United States
10 h-index
16 publications
521 citations
Stanford University
Stanford, United States
10 h-index
30 publications
808 citations
University of California, Berkeley
Berkeley, United States
10 h-index
13 publications
1.5K citations

Cornell University
Ithaca, United States
9 h-index
11 publications
403 citations
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Repository · 28 publications · 976 citations
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11 publications · 2.6K citations
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9 publications · 7K citations
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Repository · 8 publications · 183 citations
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8 publications · 645 citations
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