Funding Agency: National Institutes of Health (NIH)
Grant type: RO1
Duration: 1/10/2022 – 1/10/2026
Grant number: R01EB030130
Team leaders (Program Directors): Alison D. Gernand and Joseph Ngonzi
Other team members: Jeffery A. Goldstein, Yoel Sadovsky, Wang Z. James, Lisa Bebell, Julian Adong, Kelly Gallagher, Magee – Janet Catov, Stefan Kostadinvo, Drucilla Roberts and Dr. Fred Kaggwa from Faculty of Computing and Informatics (FCI) at MUST.
Project title: Development of a Software to Rapidly Asses Placenta Images at Birth
Project aims:
- To develop AI-based software that accurately identifies a range of placental features and diagnoses from digital images;
- To improve the reliability and robustness of the AI-based software under different conditions. The team will test the impact of the variability of factors (e.g., different cameras, lighting) on the accuracy of feature identification;
- To test and quantify improvements in software accuracy with medical data input. The team will add readily available clinical data to algorithms such as infant sex, delivery mode and birth weight to systematically quantify improvements when such data is available.
Congratulations to the team on this great grant achievement. All the best on a successful implementation process.