Early detection and outcome prediction for fatty liver (NAFLD)
NAFLD Diagnosis and Outcomes
Using AI on medical records to find which adults with fatty liver are more likely to develop serious liver problems.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Mayo Clinic Rochester NIH-funded |
| Lab location | 1 site (Rochester, United States) |
| Project ID | NIH-11247579 on NIH RePORTER |
What this research studies
You would allow researchers to use information from your medical records—like diagnoses, lab tests, medications, height/weight, and basic demographics—to look for patterns linked to fatty liver and its worsening. The team will train machine-learning models on large electronic health record datasets to spot people with NAFLD and predict who may progress to cirrhosis or other liver events. The goal is tools that can run in primary care so doctors can identify higher-risk patients earlier and tailor follow-up or treatments. Your data may help create screening flags that work across routine healthcare visits.
Who could benefit from this research
Good fit: Adults aged 21 and older whose electronic health records include relevant labs, diagnoses, medications, or primary care follow-up—especially people with obesity, diabetes, or abnormal liver tests—are ideal candidates for contributing data or participating.
Not a fit: Children, people under 21, those without accessible electronic health records, or patients with non-NAFLD liver diseases are unlikely to benefit directly from this specific project.
Why it matters
Potential benefit: If successful, this could help doctors catch risky fatty liver earlier and direct patients to closer monitoring or treatments before severe liver damage occurs.
How similar studies have performed: Other teams have used EHRs and AI to identify liver disease with promising early results, but using these methods to reliably predict long-term progression is still relatively new.
Where this research is happening
Rochester, United States
- Mayo Clinic Rochester — Rochester, United States (Active)
Researchers
- Principal investigator: Allen, Alina M — Mayo Clinic Rochester
- Study coordinator: Allen, Alina M
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.