OpenHDI · Open Health Data Impact

The Utility of Advanced Unsupervised Learning Methods to Model Dietary Intake Data

Registered study from NIH RePORTER funded projects. Evidence status: source reported.

Organisation
Icahn School of Medicine at Mount Sinai
Published
2025-09-01
Source reference
F31HL179963
Jurisdiction
United States
Licence
Public domain (US Government work, NIH RePORTER). Investigator names are not imported.

Recipient: Icahn School of Medicine at Mount Sinai (United States) · Funder: NIH NHLBI · Awarded: US$73,995 · FY2025 to FY2026 · Found via: UK Biobank

Source: https://reporter.nih.gov/project-details/11465123. Captured 2026-10-30.

Limitations: An NIH award whose title, abstract or indexed terms mention UK Biobank. A mention at funding is not evidence that the data was obtained or analysed; no access agreement is linked by this. The award total is the sum of NIH's yearly award amounts for the fiscal years found, in US dollars, and may include work unrelated to UK data.