Dominik Aronsky , M.D., Ph.D.

Associate Professor of Biomedical Informatics

Director, Academic Programs for Fellowships,

Infrastructure, and Interdisciplinary Training


Room 448 Eskind Biomedical Library

2209 Garland Ave

Nashville, TN

Phone: (615) 936-1739

Fax: (615) 936-1427

Email: dominik.aronsky@vanderbilt.edu


Dominik Aronsky, M.D., Ph.D., joined the faculty in November 2000 as an Assistant Professor in Biomedical Informatics.

Background: Dr. Aronsky completed his MD degree at the University of Berne (Switzerland). He earned a postgraduate diploma in software engineering from the Technical University Berne. His clinical work included two years of residency in anesthesia and surgery. To pursue his interest in medical informatics he was awarded an MD-PhD grant from the Swiss National Science Foundation. He earned a PhD in Medical Informatics from the University of Utah in October 2000.

Prior work: During his clinical work Dr. Aronsky investigated and published research in laparoscopic endoscopy. In medical informatics, his research focused on developing, implementing, and evaluating decision support systems for real world clinical problems. For his dissertation he developed and evaluated a population based Bayesian network for the automatic, real time identification of patients likely to have pneumonia. After identifying pneumonia patients computerized pneumonia guideline evaluation is triggered. The pneumonia research led to a number of collaborative studies such as the computerized and clinical evaluation of different pneumonia guidelines, the application of natural language processing systems for the interpretation of chest x-ray reports, the use of DNR orders in pneumonia patients, and the application of continuous quality improvement methods for coded data entry.

Interests: Dr. Aronsky is interested in interdisciplinary research with a focus on developing, implementing, integrating, and evaluating decision support systems for real time, clinical applications. He is interested in collaborating closely with clinicians and other researchers to develop and evaluate integrated systems that apply a variety of machine learning methods. He is also interested in the study design and the clinical evaluation of medical informatics systems.