Digital Health and Life Sciences Informatics have entered an era of major data transformation spurred by the use of advanced analytics and related technologies. Data-driven translational research, population health management, and precision medicine have served as the catalysts for this transformation.
With access to massive amounts of structured and unstructured patient data across a wide range of data sources, data science can aid in diagnosing patient conditions, developing new therapeutics, matching treatment with best outcomes, and predicting patients’ risk levels for disease. In a “learning healthcare system” like the University of Miami, the availability of millions of patient records means that predictive analytics can identify comparable physical symptoms in patients who are the same age, gender, ethnicity, and who display similar responses to a specific medication. By analyzing vast data sets across different systems, data science can inform healthcare decisions and transform basic and translational biomedical research. Furthermore, cutting-edge data science can also be used to understand and predict marine ecosystems and their use in the discovery of new drugs.
Combining the most impressive academic programs with one of the most extensive health care systems in all of south Florida, the University of Miami is well-positioned to harness the power of patient-record data science.
Nicholas Tsinoremas, PhD
Interim Director, IDSC Digital Health and Life Sciences Informatics
|Stephan Schürer, PhD
Director, IDSC Digital Drug Discovery
Azizi Seixas, PhD
Director, IDSC Population Health Informatics
Daniel Messinger, PhD
Director, IDSC Social and Behavioral Data Science