Wake Forest University

Type

Funder

Country

ROR

0207ad724

not unique to one org

OpenAlex

F4320309558

the anchor

Documents

32

through any edge

Papers

0

authorship edges

Awards made

33

27 grant numbers

Named as funder

32

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 Wake Forest University has funded

33 awards under 27 distinct grant numbers, across 8 documents. A further 32 documents name it as a funder without a grant number — a weaker claim, counted separately.

Accelerated and Interpretable Oblique Random Survival Forestsgrant P30AG021332 · 2023-06-30Accelerated and Interpretable Oblique Random Survival Forestsgrant UL1TR001420 · 2023-06-30De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repositorygrant UL1TR001420 · 2023-07-07Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR001420 · 2024-10-21Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR001420 · 2024-11-05Causal Inference via Electronic Health Records in the National Clinical Cohort Collaborative: Challenges and Solutions in Long COVID Researchgrant UL1TR001420 · 2025-06-08Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs.grant UL1TR001420 · 2025-07-26Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Studygrant U18DP002710 · 2020-11-07Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Studygrant 00097 · 2020-11-07Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Studygrant 1U18DP002709 · 2020-11-07

10 of 65 funding edges

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