Using digital tools to improve early detection of kidney disease
Digital Tools for Precision Nephrology
This study is working on new ways to spot early signs of a kidney condition called Collagen Type IV-Associated Nephropathy by analyzing health records, so that doctors can provide better and more personalized care to patients with chronic kidney disease.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Columbia University Health Sciences NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-10984822 on NIH RePORTER |
What this research studies
This research focuses on developing advanced methods to identify early signs of Collagen Type IV-Associated Nephropathy (COL4A-AN) through the analysis of electronic health records (EHR). By utilizing Natural Language Processing (NLP) techniques, the project aims to convert unstructured clinical data into structured information, which can help in recognizing different subtypes of chronic kidney disease (CKD). The goal is to create precise prediction models that can lead to timely and personalized interventions for patients, ultimately delaying the progression of kidney disease. This innovative approach seeks to standardize data across health systems to enhance the accuracy of diagnoses and treatment plans.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals at risk for or diagnosed with Collagen Type IV-Associated Nephropathy or other genetic subtypes of chronic kidney disease.
Not a fit: Patients with kidney diseases unrelated to Collagen Type IV or those who do not have access to electronic health records may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of kidney disease, allowing for timely interventions that may slow disease progression.
How similar studies have performed: Other research has shown promise in using electronic health records and NLP for disease detection, indicating that this approach has potential for success.
Where this research is happening
New York, United States
- Columbia University Health Sciences — New York, United States (Active)
Researchers
- Principal investigator: Nestor, Jordan Gabriela — Columbia University Health Sciences
- Study coordinator: Nestor, Jordan Gabriela
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.