Creating realistic synthetic health data for better clinical decision-making

SCH: Heterogenous, dynamic synthetic data: From algorithms to clinical applications

['FUNDING_R01'] · UNIVERSITY OF CALIFORNIA AT DAVIS · NIH-11000828

This study is working on creating smart computer programs that can make fake health data that looks like real patient information, all while keeping your privacy safe, to help improve tools that doctors use to make better decisions for patients with conditions like acute respiratory distress syndrome.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF CALIFORNIA AT DAVIS (nih funded)
Locations1 site (DAVIS, UNITED STATES)
Trial IDNIH-11000828 on ClinicalTrials.gov

What this research studies

This research focuses on developing advanced algorithms to generate synthetic health data that mimics real patient data while protecting privacy. By creating dynamic and heterogeneous datasets, the project aims to enhance the development of clinical decision support applications, particularly for conditions like acute respiratory distress syndrome. The approach addresses the challenges of accessing and deidentifying health data, which are crucial for validating AI methods in healthcare. Patients may benefit from improved clinical tools and decision-making processes that arise from this innovative data generation technique.

Who could benefit from this research

Good fit: Ideal candidates for this research are patients experiencing acute respiratory distress or related conditions requiring intensive care.

Not a fit: Patients with stable respiratory conditions or those not requiring intensive medical intervention may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more effective clinical decision-making tools that improve patient outcomes in critical care settings.

How similar studies have performed: While synthetic data has been explored in healthcare, this research aims to advance the field by developing more complex and useful datasets, making it a novel approach.

Where this research is happening

DAVIS, 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 →

Conditions: Acute Respiratory Distress Syndrome, Adult Respiratory Distress Syndrome

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.