Machine learning and Precision Medicine
I'm interested in making Medicine better utilizing machine learning models and massive medical datasets. "Precision Medicine" is Medicine, and the proper application of modern machine learning can move us away from a paradigm of treating individuals based upon population level insights, to treating individuals based upon individualized evidence and insights.
Artificial intelligence and human intelligence
I'm interested in the basic computational mechanisms behind machine learning, and particularly how insights from human learning and neuroscience might advance the field of deep learning. I'm also interested in the converse, and hope that as we better understand deep learning we'll also understand human learning and human intelligence. Our group utilizes deep learning, mathematics, and neuroscience to tackle two questions: (1) What are the basic mechanisms responsible for human intelligence? (2) How can we build better artificial intelligence?
Philosophy of medicine
I'm interested in the core philosophical foundations of medical practice. Particularly ontological ethical theories.
Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device and biotechnology companies to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their relationships with such companies.
Dr.Oermann did not report having any of the following types of financial relationships with industry during 2018 and/or 2019: consulting, scientific advisory board, industry-sponsored lectures, service on Board of Directors, participation on industry-sponsored committees, equity ownership valued at greater than 5% of a publicly traded company or any value in a privately held company. Please note that this information may differ from information posted on corporate sites due to timing or classification differences.
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