Predicting health risks in heart failure patients using advanced data analysis.
Official title: Real time risk prognostication via scalable hazard trees and forests
Funded at University of Miami School of Medicine · NIH-11063194 · Data updated 2026-11-12
This study is looking at how we can use information from wearable devices and health records to help doctors predict health risks for people with heart failure, so they can give better care and keep patients healthier.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Miami School of Medicine NIH-funded |
| Lab location | 1 site (Coral Gables, United States) |
| Project start | April 1, 2023 |
| Project end | March 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $591,396 |
| NIH project number | 5R01HL164405-03 |
| Project ID | NIH-11063194 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are heart failure patients who are listed for heart transplantation and have access to wearable health monitoring devices.
✕Less likely to help
Patients with conditions unrelated to heart failure or those not listed for transplantation may not benefit from this research.
What this research studies
This research focuses on utilizing data from wearable devices and Electronic Health Records (EHRs) to create real-time systems that can predict health risks for patients, particularly those with heart failure. By employing advanced machine learning techniques, the study aims to analyze complex health data to identify potential adverse outcomes and provide personalized risk assessments. The goal is to develop user-friendly software that can be used by healthcare providers to improve patient care and outcomes.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of health risks, allowing for timely interventions that could improve survival rates and quality of life for patients.
How similar studies have gone: Previous research has shown promise in using machine learning for health risk prediction, indicating that this approach could be effective.
Where this research is happening
-
University of Miami School of Medicine
Coral Gables, United States Active
Researchers
- Principal investigator: Ishwaran, Hemant — University of Miami School of Medicine
- Study coordinator: Ishwaran, Hemant
Related research
Other NIH-funded projects on the same topics.
-
Decoding how GAA repeats in FGF14 cause SCA27B
This project looks at why a specific DNA repeat in the FGF14 gene leads to Spinocerebellar Ataxia 27B in adults.
-
Breathing therapy to help clear brain toxins in older adults who sleep poorly
A small study will test a breathing-based therapy to boost brain toxin clearance in older adults with poor sleep patterns related to Alzheimer’s risk.
-
New retinal imaging to detect brain small vessel disease
A fast, wide-field eye imaging method will measure how tiny retinal blood vessels rhythmically flow to help detect early brain small vessel disease.
-
Understanding the Genetics Behind IBD in South Florida
This grant looks at how genes and the environment come together to influence inflammatory bowel disease in people living in South Florida.
-
MorpHiC Data Resource and Coordinating Center
A national effort to build and share a comprehensive, high-quality catalogue of how human genes affect cell function when they’re turned off, using human cellular models.
-
MorPhiC data hub for gene function in human cells
A data resource and coordinating center will organize and share information about how human genes affect cellular traits when knocked out, helping researchers understand gene functions.
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.