Using machine learning to improve analysis of electronic health records

Statistical Methods for Incorporating Machine Learning Tools in Inference and Large-Scale Surveillance using Electronic Medical Records Data

NIH-funded research University of Washington · NIH-10645177

This study is looking at how to use smart computer techniques to better understand health records, so that patients can get more accurate treatment recommendations and safer care based on a lot of data.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionUniversity of Washington NIH-funded
Lab location1 site (Seattle, United States)
Project IDNIH-10645177 on NIH RePORTER

What this research studies

This research focuses on enhancing the analysis of electronic health records (EHR) by incorporating advanced machine learning techniques. By leveraging large datasets from EHRs, the project aims to better understand the effectiveness of various treatments and monitor safety issues in diverse patient populations. The researchers will develop new statistical methods to ensure that the insights gained from these analyses are reliable and valid, ultimately improving patient care. Patients may benefit from more accurate treatment recommendations based on comprehensive data analysis.

Who could benefit from this research

Good fit: Ideal candidates for this research are patients whose treatment outcomes are recorded in electronic health records, particularly those receiving various medical interventions.

Not a fit: Patients who do not have their treatment data captured in electronic health records may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more effective and safer treatment options for patients based on robust data analysis.

How similar studies have performed: Other research has shown success in using machine learning techniques for analyzing health data, indicating that this approach is promising and not entirely novel.

Where this research is happening

Seattle, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.