Using advanced computer methods to improve health predictions from electronic health records.
Personalized Risk Predictions with Deep Learning Methods in the Presence of Missing and Biased Electronic Health Record Data
This study is working on using advanced computer techniques to make better predictions about health risks by looking at electronic health records, so that doctors can provide better care for patients, even when some information is missing or not fully accurate.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Weill Medical Coll of Cornell Univ NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-11194592 on NIH RePORTER |
What this research studies
This research focuses on enhancing the accuracy of health risk predictions by utilizing deep learning techniques to analyze electronic health records (EHRs). It addresses the challenges posed by missing and biased data in EHRs, which often do not represent the entire patient population. By developing more reliable prediction models, the research aims to provide better insights into patient health risks, ultimately leading to improved patient care. The approach involves sophisticated algorithms that can learn from complex data patterns, even when some information is incomplete or skewed.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients whose health data is recorded in electronic health records, particularly those with chronic diseases.
Not a fit: Patients without electronic health records or those who do not have chronic conditions may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate health risk assessments, enabling personalized treatment plans for patients.
How similar studies have performed: Other research has shown promise in using advanced data analysis techniques to improve health predictions, indicating that this approach has potential for success.
Where this research is happening
New York, United States
- Weill Medical Coll of Cornell Univ — New York, United States (Active)
Researchers
- Principal investigator: Zhong, Hua Judy — Weill Medical Coll of Cornell Univ
- Study coordinator: Zhong, Hua Judy
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.