Type
Funder
Country
—
Documents
19
through any edge
Papers
0
authorship edges
Awards made
20
19 grant numbers
Named as funder
19
no grant number
Identifiers
Funding
Read from the funding tables, never from the document count — that count includes authorship, so it ranks institutions, not funders.
What Health Resources and Services Administration has funded
20 awards under 19 distinct grant numbers, across 9 documents. A further 19 documents name it as a funder without a grant number — a weaker claim, counted separately.
Inferring Lexicographically-Ordered Rewards from Preferencesgrant HHSH250-2019-00001C · 2022-06-28Overcoming Confounding Bias in Causal Discovery Using Minimum Redundancy and Maximum Relevancy Constraintgrant GR301281 · 2024-01-01Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relategrant 234-2005-370011C · 2024-05-23Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relategrant 370011C · 2024-05-23Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC00001 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC00007 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC22684 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC28844 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC33154 · 2025-02-20Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consentgrant U03MC33156 · 2025-02-20
10 of 39 funding edges