Improving sepsis detection and classification using hospital electronic health records
Integrated Detection and Classification of Sepsis via Tensor Methods Using EHR
This project uses hospital electronic health records and advanced math to spot sepsis earlier and group adult patients into types to help guide treatment.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project ID | NIH-11332721 on NIH RePORTER |
What this research studies
You would be part of a project where researchers analyze large numbers of hospital electronic health records from adult patients to find patterns linked to sepsis. They convert the data into a three-way tensor format that captures patient, clinical features, and time, then apply advanced mathematical and machine‑learning methods to handle sparse and changing data. The goal is to detect sepsis earlier, sort patients into distinct disease types or phenotypes, and suggest more personalized treatment paths. Work is done with existing EHR data across participating hospitals, so there is no new medical procedure for most patients beyond data use or routine care.
Who could benefit from this research
Good fit: Adults aged 21 and over who are hospitalized or receiving care at participating hospitals, especially those with infections or suspected sepsis, are the main candidates for inclusion.
Not a fit: Children under 21, people treated outside participating hospital systems, or anyone whose records are not included or shared would be unlikely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this could lead to earlier warnings for sepsis and more tailored treatments, potentially reducing deaths and complications.
How similar studies have performed: Previous machine‑learning work on EHRs has sometimes improved early sepsis alerts but produced mixed clinical outcomes, and the tensor-based approach here is relatively new with limited prior testing.
Where this research is happening
Durham, United States
- Duke University — Durham, United States (Active)
Researchers
- Principal investigator: Zhang, Anru — Duke University
- Study coordinator: Zhang, Anru
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.