Multimodal AI to improve genetic diagnosis of congenital heart disease

Who could benefit from this research

What this research studies

This project develops an AI system that combines data from heart imaging, medical records, and whole-genome sequencing to pinpoint genes likely involved in congenital heart disease. It aims to prioritize candidate genes and automatically identify likely disease-causing variants, making genetic diagnosis faster and more accurate. The work will be designed with input from patients, families, clinicians, and other stakeholders to address ethical considerations and fit into clinical workflows at Baylor College of Medicine. If successful, it could lead to more personalized prognoses and treatment plans for children with CHD.

Why it matters

Where this research is happening

• Baylor College of Medicine
  Houston, United States Active

Researchers

• Principal investigator: Milosavljevic, Aleksandar — Baylor College of Medicine
• Study coordinator: Milosavljevic, Aleksandar

Related research

Other NIH-funded projects on the same topics.

• Multimodal AI to improve genetic diagnosis of congenital heart disease

  A new AI tool uses multiple types of patient data to help doctors find genetic causes of congenital heart disease more accurately.

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• Brain injury risk in preterm babies with heart disease and how surgery choices affect their brains

  This project follows newborns with congenital heart disease born early to understand how their brains are affected and how different surgical approaches might influence outcomes.

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• Newborn brain injury risk during birth transition in babies with congenital heart defects

  This project will look at how circulation changes around birth affect newborn brain health in babies with transposition of the great arteries.

  NIH research University of California, San Francisco · San Francisco, United States · NIH-11474556

• Heart development study using patient stem cells to understand NOTCH1 and congenital heart disease

  A study using patient-derived stem cells and genome editing to learn how NOTCH1 affects early heart development and congenital heart defects in humans.

  NIH research Research Inst Nationwide Children's Hosp · Columbus, United States · NIH-11448014

• AI-powered echocardiography to spot common heart defects in newborns

  A new AI tool analyzes infant heart ultrasound images to help non-specialist health workers identify five common, treatable heart defects early.

  NIH research Health Research Foundation · Buea, CAMEROON · NIH-11446295

• Genetic clues to congenital heart defects and outcomes

  This grant studies how genetic differences contribute to congenital heart defects (CHD) and how these variations affect health over time, with patient data from a large biobank and health records.

  NIH research Icahn School of Medicine at Mount Sinai · New York, United States · NIH-11422502

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.