Washington University in St. Louis

Type

Funder

Country

ROR

01yc7t268

not unique to one org

OpenAlex

F4320309650

the anchor

Documents

36

through any edge

Papers

0

authorship edges

Awards made

12

3 grant numbers

Named as funder

36

no grant number

Funding

Read from the funding tables, never from the document count — that count includes authorship, so it ranks institutions, not funders.

What Washington University in St. Louis has funded

12 awards under 3 distinct grant numbers, across 4 documents. A further 36 documents name it as a funder without a grant number — a weaker claim, counted separately.

De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repositorygrant UL1TR001422 · 2023-07-07De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repositorygrant UL1TR002345 · 2023-07-07De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repositorygrant UL1TR002489 · 2023-07-07Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR001422 · 2024-10-21Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR002345 · 2024-10-21Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR002489 · 2024-10-21Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR001422 · 2024-11-05Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR002345 · 2024-11-05Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR002489 · 2024-11-05Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs.grant UL1TR001422 · 2025-07-26

10 of 48 funding edges

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