The Henry M. Jackson Foundation for the Advancement of Military Medicine

Advancing Military Medicine

Search Results - respiratory+distress

2 Results Sort By:
Use of Machine Learning Models for Prediction of Clinical Outcomes (HJF 529-18)
Background Individuals exposed to physical trauma, including battlefield injuries and major accidents, are at elevated risk of severe complications. Existing diagnostic approaches can make it difficult to accurately quantify clinical risk and guide treatment decisions, particularly in environments where advanced diagnostics are unavailable. Early identification...
Published: 7/16/2026   |   Updated: 5/28/2026   |   Inventor(s): Seth Schobel-McHugh, Matthew Bradley
Keywords(s): Biomarker, Critical Care, Diagnostics, Machine Learning, Random Forest Model, Respiratory, Respiratory Distress, Sepsis, Traumatic Brain Injury
Category(s): Diagnostic
System and Method for Predicting Pulmonary and Other Complications Following Rib Fractures - (HJF 690-24)
Introduction Scientists at the Henry M. Jackson Foundation (HJF), the Uniformed Services University of the Health Sciences (USUHS), and Duke University (Duke) have developed innovative systems, methods, and computational models designed to predict clinical complications such as acute lung injury (ALI), acute kidney injury (AKI), pneumonia, and respiratory...
Published: 7/6/2026   |   Updated: 12/19/2025   |   Inventor(s): Joseph Fernandez-Moure, Seth Schobel-McHugh, Scott Grey, Renhua Li, Eric Elster
Keywords(s): Acute Kidney Injury (AKI), Acute Lung Injury (ALI), Biomarker, CDST, Chemokines, Cytokines, Immune Response Dynamics, Injury Trauma Prediction, Machine Learning, Personalized Treatment, Respiratory Distress
Category(s): Diagnostic