The Power and Potential of Open Science and the Future of MIMIC: Predictive and Prognostic Modeling from Electronic Health Records
Date: Oct 13, 2017
Time: 11:00 – 12:00
Place: E2-2, #Basement Large Lecture Room
There is a growing appreciation of the potential of the secondary analysis of health data for evidence based research and improving treatment outcomes and performance. However, most of the world’s data is locked in proprietary datasets, limiting who can learn and who can benefit and hindering research. Our progress over the past decade proves that there is broad appreciation of the value of open data and wide consensus that it accelerates knowledge discovery, and promotes the reliability and reproducibility of research. MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, high-resolution database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework.
Kenneth E. Paik, MD MBA MMSc
MIT Laboratory for Computational Physiology Institute for Medical Engineering & Science
Harvard-MIT Division of Health Sciences & Technology
Dr. Kenneth Paik is a clinical informatician driving quality improvement in healthcare through technology innovation, combining a multidisciplinary background in medicine, machine learning, business management, and technology strategy. He is a research scientist at the MIT Laboratory for Computational Physiology investigating the secondary analysis of health data and building intelligent decision support systems. As the co-director of Sana, he leads programs and projects accelerating digital innovations in global health for resource-limited settings. Dr. Paik received his medical training from the Georgetown University School of Medicine and completed a postdoctoral fellowship in clinical informatics from Harvard Medical School at the Massachusetts General Hospital Lab of Computer Science.