Using advanced machine learning to analyze diverse healthcare data

Multi-modal unsupervised embeddings to advance machine learning in healthcare

['FUNDING_R01'] · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · NIH-11019858

This study is looking at how to combine different types of health information, like medical records and test results, to help doctors make better decisions for patients, so you could get more accurate diagnoses and treatments.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorICAHN SCHOOL OF MEDICINE AT MOUNT SINAI (nih funded)
Locations1 site (NEW YORK, UNITED STATES)
Trial IDNIH-11019858 on ClinicalTrials.gov

What this research studies

This research focuses on integrating various types of biomedical data, such as electronic health records, molecular data, and imaging, to improve healthcare outcomes. By employing unsupervised machine learning techniques, the project aims to create low-dimensional representations of medical concepts and patient histories from large datasets. This approach seeks to eliminate biases and enhance the scalability and effectiveness of predictive models in healthcare. Patients may benefit from improved diagnostic and treatment strategies derived from these advanced data analyses.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals whose health data can be integrated from various sources, including electronic health records and biobanks.

Not a fit: Patients with limited or no access to electronic health records or those not represented in biobanks may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more accurate and personalized healthcare solutions for patients.

How similar studies have performed: Other research has shown promise in using machine learning to analyze healthcare data, indicating that this approach could lead to significant advancements.

Where this research is happening

NEW YORK, 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.

View on NIH RePORTER →

Last reviewed 2026-05-15 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.