2026 Research Award - AI-Enabled Early Detection and Risk Stratification for Ovarian Cancer
Funding Amount
$50,000
Deadline
Deadline not published
Grant Type
Foundation
Deadline history & next window
- Cycle
- Annual
- Tracked since
- April 2026
Source: the cycle recorded on this listing. Confirm dates with the funder.
Can we apply?
Check your organization against each line. Taken from the listing; confirm with the funder's guidelines.
Other requirements
- Oregon (US)
Overview
Focus Area: Early detection and risk stratification for ovarian cancer using artificial intelligence
Project Description
This award supports an innovative research project that leverages artificial intelligence and real-world clinical data to improve early detection of ovarian cancer. The study integrates longitudinal electronic medical records with genomic information to develop advanced risk-prediction models capable of identifying ovarian cancer earlier, when outcomes are most favorable. By focusing on dynamic risk stratification in symptomatic women, this work has the potential to inform future clinical strategies and address critical unmet needs in ovarian cancer care.
Investigators
- Dr. Brady Bernard | Providence Portland Cancer Institute
- Dr. Jackilen Shannon | OHSU Knight Cancer Institute
- Dr. Christopher Darus | Providence Portland Cancer Institute
Mission Alignment
The SHOC Foundation supports diverse portfolios of ovarian cancer research spanning early detection, novel therapeutics, survivorship, and equity. The foundation invests in innovative science, translational discovery, and supports the next generation of women investigators.
What Sherie Hildreth Ovarian Cancer Foundation actually gave
Source: IRS Form 990, 2023 — the most recent filing with itemized grants
- Grants in 2023
- 1
- Total given
- $75K
- Median grant
- $75K
- By dollars: Oregon 100%. Top recipient cities: Portland, OR.
Example grants
Ohsu Foundation 75000 · Portland, OR
Cancer research
$75K
Focus Areas & Funding Uses
Fields of Work
- Cancer
- Science research
Categories
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