Tufts Medical Center

Type

Funder

Country

ROR

002hsbm82

not unique to one org

OpenAlex

F4320309394

the anchor

Documents

8

through any edge

Papers

0

authorship edges

Awards made

10

2 grant numbers

Named as funder

8

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 Tufts Medical Center has funded

10 awards under 2 distinct grant numbers, across 5 documents. A further 8 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 UL1TR001425 · 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 UL1TR002544 · 2023-07-07Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR001425 · 2024-10-21Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR002544 · 2024-10-21Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR001425 · 2024-11-05Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programsgrant UL1TR002544 · 2024-11-05Causal Inference via Electronic Health Records in the National Clinical Cohort Collaborative: Challenges and Solutions in Long COVID Researchgrant UL1TR001425 · 2025-06-08Causal Inference via Electronic Health Records in the National Clinical Cohort Collaborative: Challenges and Solutions in Long COVID Researchgrant UL1TR002544 · 2025-06-08Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs.grant UL1TR001425 · 2025-07-26Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs.grant UL1TR002544 · 2025-07-26

10 of 18 funding edges

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