SAEMF Research Training Grant - $299,932

"Pulmonary Embolism Pre-Test Probability and Severity Estimation Using AI"

Pulmonary Embolism (PE) is the third leading cause of cardiovascular death and is challenging to diagnose. Our study will use a largest available database of patients who have been evaluated for PE to create machine learning models to estimate the probability that a patient has a PE and to determine how severe a PE is once it is diagnosed.

Recipient(s)

  • Drew Birrenkott, MD, DPhil

    Drew Birrenkott, MD, DPhil

    Mass General Brigham

    "Pulmonary Embolism Pre-Test Probability and Severity Estimation Using AI"

    Drew Birrenkott, MD, DPhil, is an attending emergency physician and fellow in clinical innovation and research translation in vascular emergencies in the Mass General Brigham Department of Emergency Medicine and Harvard Medical School. Upon completion of his fellowship, he will join the department as faculty in the Center for Vascular Emergencies.

    Dr. Birrenkott earned his Bachelor of Science in biomedical engineering, biochemistry, and political science from the University of Wisconsin–Madison. He completed a Doctor of Philosophy in engineering science at the University of Oxford as a Rhodes Scholar and received his medical degree from Stanford University. He completed residency training at the Harvard Affiliated Emergency Medicine Residency at Massachusetts General Hospital and Brigham and Women’s Hospital.

    His research interests focus on machine learning and predictive modeling in acute care, with a particular emphasis on pulmonary embolism. Dr. Birrenkott serves as principal investigator on a project developing artificial intelligence and proteomics-based models to predict the probability and severity of pulmonary embolism in emergency department patients.