Improving care for sepsis patients using advanced algorithms

Implementation of Continuum of Care Sepsis Phenotyping and Risk Stratification

['FUNDING_OTHER'] · UNIVERSITY OF CALIFORNIA, SAN DIEGO · NIH-11085076

This study is looking to improve how we treat people with sepsis by using smart computer programs to better understand and manage their care, making it more personalized for each patient.

Quick facts

Phase['FUNDING_OTHER']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF CALIFORNIA, SAN DIEGO (nih funded)
Locations1 site (LA JOLLA, UNITED STATES)
Trial IDNIH-11085076 on ClinicalTrials.gov

What this research studies

This research focuses on enhancing the treatment of sepsis patients by implementing deep-learning algorithms in clinical settings. The project aims to develop and apply innovative machine-learning techniques to better identify and manage sepsis cases, tailoring care to individual patient needs rather than using a generic approach. Dr. Gabriel Wardi, along with a team of experts, will work on designing effective studies and utilizing statistical methods to ensure the algorithms are beneficial in real-time clinical practice. The goal is to improve patient outcomes through more precise and personalized care strategies.

Who could benefit from this research

Good fit: Ideal candidates for this research are patients diagnosed with sepsis or at high risk of developing sepsis, particularly those receiving care in emergency departments.

Not a fit: Patients who do not have sepsis or are not at risk for sepsis may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to significantly improved treatment protocols for sepsis, potentially saving lives and reducing complications.

How similar studies have performed: Previous research has shown promise in using machine learning for predicting and managing sepsis, indicating that this approach could be effective.

Where this research is happening

LA JOLLA, 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.