Type
Funder
Country
—
Documents
9
through any edge
Papers
0
authorship edges
Awards made
13
10 grant numbers
Named as funder
9
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 Kræftens Bekæmpelse has funded
13 awards under 10 distinct grant numbers, across 7 documents. A further 9 documents name it as a funder without a grant number — a weaker claim, counted separately.
Lexical Stability of Psychiatric Clinical Notes from Electronic Health Records over a Decadegrant R283-A16461 · 2022-09-06False Responses From Artificial Intelligence Models Are Not Hallucinationsgrant R283-A16461 · 2023-05-23Predicting cardiovascular disease in patients with mental illness using machine learninggrant R283-A16461 · 2025-01-01A deep learning framework for efficient pathology image analysisgrant 1000143 · 2026-07-01A deep learning framework for efficient pathology image analysisgrant 14136 · 2026-07-01A deep learning framework for efficient pathology image analysisgrant C8221/A29017 · 2026-07-01A deep learning framework for efficient pathology image analysisgrant C8221/A29017 to EPIC-Oxford · 2026-07-01A deep learning framework for efficient pathology image analysisgrant MR/M012190/1 · 2026-07-01Deep Learning‐Based Tumor Cell Classification in Lung Adenocarcinoma With a Case‐by‐Case Human‐in‐the‐Loop Approachgrant R352‐A20551 · 2026-04-01Receiving Information on Machine Learning‐Based Clinical Decision Support Systems in Psychiatric Services Increases Staff Trust in These Systems: A Randomized Survey Experimentgrant R283-A16461 · 2025-02-11
10 of 22 funding edges