I-Corps: Translation potential of computer modeling and machine learning for analyzing Doppler ultrasound data to predict placental insufficiency Grant uri icon

abstract

  • Placental insufficiency, a condition where the placenta fails to deliver an adequate supply of nutrients and oxygen to the fetus, affects 6 million pregnancies in the United States, and placental abnormalities are the most prevalent findings in stillbirth, with intrauterine fetal demise being the 5th leading cause of death worldwide. Additionally, for expecting mothers, placental insufficiency can lead to complications such as obstetric hemorrhaging, permanent damage to the uterine lining, and death. Current diagnostic methods for placental insufficiency are reactive, relying on symptom presentation and/or emergencies, which limits the ability to prevent adverse outcomes and fetal death. My lab is developing a technology that leverages advanced computer modeling underpinned by our previously funded NSF grant and a novel machine learning (ML) approach for analyzing Doppler ultrasound data to accurately predict the likelihood of placental insufficiency. Therefore, our technology provides clinicians with a new decision support system to identify and engage at-risk mothers to improve pregnancy outcomes. Engaging in the National I-Corps program will greatly boost our alignment with market needs by offering essential feedback and perspectives from industry leaders and potential customers. The program?s funding will support our participation in key conferences, where we?ll have the opportunity to network, confirm our target audience, and fine-tune our strategy for market entry. This experience will be vital for building a persuasive case for future funding, whether at the national level (such as SBIR) or state level, and will help us secure the resources needed to expand our operations and achieve broad market success.

date/time interval

  • April 2025 - March 2026