(New York, NY – April 19, 2021) – The Graduate School of Biomedical Sciences at the Icahn School of Medicine at Mount Sinai will offer a new PhD concentration in Artificial Intelligence and Emerging Technologies in Medicine (AIET) as part of its PhD in Biomedical Sciences program. Hayit Greenspan, PhD and Alan C. Seifert, PhD are the newly appointed AIET Co-Directors. Application will be open from late August through December 1, 2021 for enrollment in the fall of 2022.
“The transformative impact of artificial intelligence and other emerging technologies in medicine is just beginning. We are now on the frontier of more accurately identifying the indicators of disease and opening up new vistas for treatment of illness in real-time,” said Dennis S. Charney, MD, Anne and Joel Ehrenkranz Dean of the Icahn School of Medicine at Mount Sinai and President for Academic Affairs of the Mount Sinai Health System. “Establishing this concentration is part of an expanding institutional commitment at Mount Sinai to advance this critically important area that will be a game-changer for physicians in their ability to provide better diagnose and care for their patients.
“The Artificial Intelligence and Emerging Technologies PhD concentration will create vital new opportunities to train the research scientists of tomorrow in assimilating innovative, cutting-edge technologies to advance drug discovery and a variety of clinical applications” said Marta Filizola, PhD, Dean of the Graduate School of Biomedical Sciences and Sharon and Frederick Klingenstein/Nathan Kase, MD Professor of Pharmacological Sciences at Icahn Mount Sinai. “Artificial intelligence and several other powerful technologies such as medical devices, robotic machines, and sensors are paving the way for a new era of biomedical research, offering unparalleled opportunities to improve human health. This new training area, along with other similar initiatives, is placing Mount Sinai at the leading edge of this emerging scientific field to enhance health and well-being of people everywhere.”
The answers to many fundamental questions in medicine and biology currently lie buried inside data collections that are too large and heterogeneous to be stored, curated, analyzed, and visualized by traditional approaches. “Future biomedical researchers will need to be equipped with the necessary skill sets to tackle escalating complexity in medicine,” said Thomas J. Fuchs, DSc, Icahn Mount Sinai’s newly appointed Dean of Artificial Intelligence and Human Health, Co-Director of the Hasso Plattner Institute for Digital Health at Mount Sinai, and an internationally renowned scientist in the field of computational pathology. “Not only will this new generation of professionals need to receive foundational education in the use of information systems, but they will need to learn how to develop and interpret predictive diagnostic and therapeutic models using a variety of machine learning tools based on statistics and probability theory, drawing upon quantitative fields such as computer science, mathematics, theoretical physics, theoretical/computational chemistry, and digital engineering.”
Equally vital in this PhD concentration is the extension of Mount Sinai’s exemplary focus on diversity of people and perspectives. One such effort includes evaluating the potential dangers of embedding race into the basic data and decisions of health care, which could perpetuate or even amplify race-based health inequities. “The new AIET PhD concentration is part of a larger effort to develop and implement new tools for faster, less expensive, and more effective drug discovery using patient-driven biology and a wide range of biological and simulation data collected at unprecedented scales across numerous departments and institutes within the Mount Sinai Health System,” said Eric J. Nestler, MD, PhD, Dean for Academic and Scientific affairs, and Director of The Friedman Brain Institute, Nash Family Professor of Neuroscience, and Dean for Academic and Scientific Affairs at Icahn Mount Sinai. This new training area will also work in close conjunction with the Biomedical Engineering and Imaging Institute, led by Zahi A. Fayad, PhD, leveraging Mount Sinai’s renowned imaging and nanomedicine programs to develop novel medical inventions in the fields of imaging, nanomedicine, artificial intelligence, and computer vision technologies such as virtual reality, augmented, and extended reality.
This AIET training area further leverages existing relationships with several well-regarded higher education institutions outside Mount Sinai to offer complementary technical expertise to expand collaborative research and enrichment opportunities for trainees and faculty. Mount Sinai’s success in developing translational research will now be accelerated with the new Artificial Intelligence and Emerging Technologies in Medicine PhD concentration.
###
About the Mount Sinai Health System
The Mount Sinai Health System is New York City’s largest academic medical system, encompassing eight hospitals, a leading medical school, and a vast network of ambulatory practices throughout the greater New York region. Mount Sinai is a national and international source of unrivaled education, translational research and discovery, and collaborative clinical leadership ensuring that we deliver the highest quality care—from prevention to treatment of the most serious and complex human diseases. The Health System includes more than 7,200 physicians and features a robust and continually expanding network of multispecialty services, including more than 400 ambulatory practice locations throughout the five boroughs of New York City, Westchester, and Long Island. The Mount Sinai Hospital is ranked No. 14 on U.S. News & World Report‘s “Honor Roll” of the Top 20 Best Hospitals in the country and the Icahn School of Medicine as one of the Top 20 Best Medical Schools in country. Mount Sinai Health System hospitals are consistently ranked regionally by specialty by U.S. News & World Report.
For more information, visit https://www.mountsinai.org or find Mount Sinai on Facebook, Twitter and YouTube.
