Using machine learning to identify children affected by prenatal alcohol exposure
Applying Machine Learning in the Prediction and Identification of Children Affected by Prenatal Alcohol Exposure
This study is looking at how we can better identify children with fetal alcohol spectrum disorders (FASD) by using advanced computer techniques to spot subtle signs that might be missed by regular check-ups, helping to ensure these kids get the support they need as early as possible.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Diego NIH-funded |
| Lab location | 1 site (La Jolla, United States) |
| Project ID | NIH-10690471 on NIH RePORTER |
What this research studies
This research focuses on fetal alcohol spectrum disorders (FASD), which result from prenatal alcohol exposure and can lead to lifelong disabilities. The study aims to improve the diagnosis of FASD by utilizing machine learning techniques to analyze complex data sets. By identifying subtle physical features and neurodevelopmental markers, the research seeks to predict and characterize children with FASD more accurately than traditional clinical methods. This could lead to earlier diagnosis and intervention, ultimately improving outcomes for affected children.
Who could benefit from this research
Good fit: Ideal candidates for this research include children who may have been exposed to alcohol in utero and exhibit developmental concerns.
Not a fit: Patients who have not been exposed to alcohol during pregnancy or do not exhibit any developmental issues may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of FASD, allowing for timely interventions that improve the quality of life for affected children.
How similar studies have performed: Other research has shown promise in using machine learning for diagnostic purposes in various medical fields, suggesting potential success for this innovative approach in identifying FASD.
Where this research is happening
La Jolla, United States
- University of California, San Diego — La Jolla, United States (Active)
Researchers
- Principal investigator: Bandoli, Gretchen E. — University of California, San Diego
- Study coordinator: Bandoli, Gretchen E.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.