Using machine learning to predict individual risk of acute kidney injury
Identifying Personalized Risk of Acute Kidney Injury with Machine Learning
['FUNDING_R01'] · UNIVERSITY OF FLORIDA · NIH-10992250
This study is looking at how to better predict the risk of kidney problems in patients in the hospital by using smart computer techniques, so doctors can give more personalized care based on each person's health history.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF FLORIDA (nih funded) |
| Locations | 1 site (GAINESVILLE, UNITED STATES) |
| Trial ID | NIH-10992250 on ClinicalTrials.gov |
What this research studies
This research focuses on understanding and predicting the risk of acute kidney injury (AKI) in hospitalized patients using advanced machine learning techniques. By analyzing complex electronic health record data, the study aims to develop personalized risk models that take into account the unique health profiles of individual patients rather than relying on generalized predictions. This approach seeks to improve the accuracy of AKI risk assessments, enabling healthcare providers to tailor interventions and treatments more effectively. The research will involve collecting and analyzing data from various patient cohorts to refine these predictive models.
Who could benefit from this research
Good fit: Ideal candidates for this research include hospitalized patients who are at risk of developing acute kidney injury due to various underlying health conditions.
Not a fit: Patients who are not hospitalized or do not have risk factors for acute kidney injury may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of acute kidney injury, allowing for timely and personalized treatment interventions that could save lives.
How similar studies have performed: Previous research has shown success in using machine learning for disease risk predictions, indicating that this approach has potential for effective application in predicting acute kidney injury.
Where this research is happening
GAINESVILLE, UNITED STATES
- UNIVERSITY OF FLORIDA — GAINESVILLE, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: LIU, MEI — UNIVERSITY OF FLORIDA
- Study coordinator: LIU, MEI
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.