Using machine learning to predict heart disease risk in women with pregnancy complications

Leveraging machine learning for cardiovascular disease risk prediction and prevention in women with a history of adverse pregnancy outcomes

NIH-funded research Brigham and Women's Hospital · NIH-10996161

This study is looking to help women who have had tough pregnancies by figuring out which ones might be more likely to have heart problems later on, so doctors can give them the right support and care they need.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionBrigham and Women's Hospital NIH-funded
Lab location1 site (Boston, United States)
Project IDNIH-10996161 on NIH RePORTER

What this research studies

This research aims to identify women who have experienced adverse pregnancy outcomes (APOs) and are at a higher risk for cardiovascular disease (CVD) later in life. By leveraging machine learning techniques, the study will analyze various factors such as individual APOs, delivery complications, and maternal demographics to create a risk classification system. This system will help healthcare providers better understand which women need closer monitoring and intervention after experiencing an APO. The goal is to develop a clinical decision support tool that can guide care and improve health outcomes for these women.

Who could benefit from this research

Good fit: Ideal candidates for this research are women who have experienced adverse pregnancy outcomes such as preeclampsia, gestational diabetes, or preterm delivery.

Not a fit: Patients who have not experienced any adverse pregnancy outcomes or who do not have a history of cardiovascular disease may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to improved risk assessment and prevention strategies for cardiovascular disease in women with a history of adverse pregnancy outcomes.

How similar studies have performed: Other research has shown promise in using machine learning for risk prediction in various health conditions, suggesting that this approach could be effective in this context as well.

Where this research is happening

Boston, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Conditions adult onset diabetesAdult-Onset Diabetes Mellitus
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.