Icahn School of Medicine at Mount Sinai to Establish World Class Center for Artificial Intelligence

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Dennis S. Charney, MD, Anne and Joel Ehrenkranz Dean of the Icahn School of Medicine, and President for Academic Affairs for the Mount Sinai Health System
Credit: Mount Sinai Health System

The Icahn School of Medicine at Mount Sinai today announced the launch of a new center dedicated to advancing the delivery of health care through research, development, and implementation of innovative artificial intelligence tools and technologies. The Hamilton and Amabel James Center for Artificial Intelligence and Human Health in Manhattan will combine artificial intelligence with data science and genomics in a standalone site. The building will enable researchers to enhance their understanding, diagnosis, and treatment of human diseases—including the most debilitating—and promote improved health and well-being.

Made possible by a generous donation from Hamilton Evans ‘Tony’ and Amabel James, the interdisciplinary center is projected to open in late 2021. Mr. James is the Executive Vice Chairman of Blackstone, a New York-based investment firm. The new Center will open with approximately 40 principal investigators, and 250 graduate students, postdoctoral fellows, computer scientists, and support staff.

“Mount Sinai has consistently been at the forefront of advancing health care across medical disciplines and this initiative represents our next step forward in building on that legacy,” said Kenneth L. Davis, MD, President and Chief Executive Officer of the Mount Sinai Health System. “We see the potential of artificial intelligence to radically transform the care that patients receive, and we want to shape and lead this effort. We are grateful to Mr. and Mrs. James for their generous gift, which will create a hub where our talented researchers can collaborate in unprecedented ways and bring forward ideas and innovative technologies that achieve better outcomes for our patients.”

“Artificial Intelligence and machine learning are spurring innovation across many different fields, but perhaps most significantly in health care,” Mr. James said. “Mount Sinai has proven itself a pioneer in data mining to improve patient diagnosis and treatment, and I am pleased to support its mission and accelerate the development of cutting-edge therapies and technologies that have the potential to change lives around the world.”

Dennis S. Charney, Anne and Joel Ehrenkranz Dean of the Icahn School of Medicine, and President for Academic Affairs for the Mount Sinai Health System, said, “We are looking at a future where artificial intelligence has the capacity to completely disrupt health care and Mount Sinai is going to be at the forefront of that revolution, driving the conversation, engaging stakeholders worldwide in developing solutions, and making this bold future a reality.”

Mount Sinai clinicians and investigators have been early adopters of artificial intelligence and currently use the technology in many different initiatives in precision medicine. AI technology is helping to characterize tissue samples of patients with prostate cancer, for example, and is being used to assist Mount Sinai doctors in identifying and prioritizing patients at risk for developing diseases and hazards such as falling.

The Hamilton and Amabel James Center for Artificial Intelligence and Human Health will focus on three key areas:

Center for Genomic Health— The new Center for Genomic Health—to be housed in the new Center for Artificial Intelligence and Human Health building—is accelerating the integration of genomics into clinical care throughout the Mount Sinai Health System. “Our goal is to use artificial intelligence to translate vast knowledge from deep databases of genomic information to improve the lives of every patient at Mount Sinai,” said Eimear Kenny, PhD, Founding Director of the Center for Genomic Health and Associate Professor of Medicine, (General Internal Medicine), and Genetics and Genomic Sciences. “The new building will bring together a generation of scientists and physicians who are trained in big data and artificial intelligence—tools that can that can enable the development of precise genomic tests and increasingly sophisticated ways to integrate genomic information into routine patient care,” said Noura Abul-Husn, MD, PhD, Clinical Director of the Center for Genomic Health and Senior Faculty of Medicine, (General Internal Medicine), and Genetics and Genomic Sciences at Icahn School of Medicine at Mount Sinai.

Integrative Omics and Multi-Scale Disease Modeling— Artificial intelligence and machine learning approaches developed at the Icahn Institute have been extensively used for identification of novel pathways, drug targets, and therapies for complex human diseases such as cancer, Alzheimer’s, schizophrenia, obesity, diabetes, inflammatory bowel disease, and cardiovascular disease. Researchers will combine insights in genomics—including state-of-the-art single-cell genomic data—with ‘omics,’ such as epigenomics, pharmacogenomics, and exposomics, and integrate this information with patient health records and data originating from wearable devices in order to model the molecular, cellular, and circuit networks that facilitate disease progression. “Novel data-driven predictions will be tightly integrated with high-throughput experiments to validate the therapeutic potential of each prediction,” said Adam Margolin, PhD, Professor and Chair of the Department of Genetics and Genomic Sciences and Senior Associate Dean of Precision Medicine at Mount Sinai. “Clinical experts in key disease areas will work side-by-side with data scientists to translate the most promising therapies to benefit patients. We have the potential to transform the way care givers deliver cost-effective, high quality health care to their patients, far beyond providing simple diagnoses. Mount Sinai wants to be on the frontlines of discovery.”

Precision Imaging—Researchers will use artificial intelligence to enhance the diagnostic power of imaging technologies—X-ray, MRI, CT, and PET—and molecular imaging, and accelerate the development of therapies. “We see a huge potential in using algorithms to automate the image interpretation and to acquire images much more quickly at high resolution – so that we can better detect disease and make it less burdensome for the patient,” said Zahi Fayad, PhD, Director of the Translational and Molecular Imaging Institute, and Vice Chair for Research for the Department of Radiology, at Mount Sinai. Dr. Fayad plans to broaden the scope of the Translational and Molecular Imaging Institute by recruiting more engineers and scientists who will create new methods to aid in the diagnosis and early detection of disease, treatment protocol development, drug development, and personalized medicine. Dr. Fayad added, “In addition to AI, we envision advance capabilities in two important areas: computer vision and augmented reality, and next generation medical technology enabling development of new medical devices, sensors and robotics.”

By bringing a cross-section of researchers together in one dedicated space, the new Hamilton and Amabel James Center for Artificial Intelligence and Human Health is expected to foster ideas that will significantly advance treatments.

To date, Mount Sinai has made progress with AI in many areas:

In 2016, researchers led by Joel Dudley, PhD, Director of the Institute for Next Generation Healthcare and the Co-Director of the newly formed Hasso Plattner Institute for Digital Health at Mount Sinai, used an advanced AI algorithm to improve prediction of diseases by analyzing de-identified data from patients across the Mount Sinai Health System. In the study published in Scientific Reports, Dr. Dudley and his colleagues found that their algorithm significantly outperformed evaluations based on raw data from electronic health records (EHR) and had impressive results in predicting severe diabetes, schizophrenia, and various cancers. “The findings indicated that using artificial intelligence and applied learning with EHRs can offer improved clinical predictions and help augment decision making by patients and their health care providers,” said Dr. Dudley, who is also Professor of Genetics and Genomic Sciences and Executive Vice President for Precision Health for the Mount Sinai Health System. “Wearable and other digital technologies can also enhance data from EHRs and lead to predictive and preventive health solutions.” The Hasso Plattner Institute, co-led by Erwin P. Bottinger, MD, Professor of Digital Health-Personalized Medicine, Hasso Plattner Institute, University of Potsdam, Germany, will develop digital technologies and wearable devices with Dr. Dudley.

Mount Sinai pathologists currently use artificial intelligence to characterize tissue samples in patients with certain diseases, including prostate and breast cancer, to more accurately predict the course of the disease; as well as to recognize and quantify accumulation of abnormal proteins, such as those in Alzheimer’s disease. “Our goal is to provide a precise mathematical approach to classifying and treating disease, which assists our clinicians with information for effective patient care and health management,” said Carlos Cordon-Cardo, MD, PhD, Director of the Center for Computational and Systems Pathology and Precise Diagnostics” (Precise Dx); Chair of the Department of Pathology; and Professor of Pathology, Genetics and Genomic Sciences, and Oncological Sciences at the Icahn School of Medicine at Mount Sinai. “By refining diagnoses, we can save patients from unnecessary treatments and improve outcomes.”

Mount Sinai’s AI-powered system assists clinicians in identifying and prioritizing patients at risk for conditions such as cardiopulmonary deterioration, malnutrition, and falls. Developed by the Clinical Data Science team, and assembled by David Reich, MD, President and Chief Operating Officer of The Mount Sinai Hospital, the system supports clinical decision making for thousands of patients each day. As the algorithms continue to “learn” from real-time data, their accuracy and performance improves.

In the Department of Population Health, Niyum Gandhi, Executive Vice President and Chief Population Health Officer of the Mount Sinai Health System, has been using machine learning algorithms to mine data that identifies patients who are at risk for unplanned admissions to Mount Sinai hospitals among our 500,000 patient population health program. “Artificial intelligence has enabled us to be more sophisticated in how we identify patients who would benefit from the interventions and solutions we can provide,” said Mr. Gandhi, who is overseeing Mount Sinai’s transition to a delivery model focused on value and risk-based population health. “It enables us to bring more science to what we do and we are now looking to expand our use of predictive modeling to other utilization metrics, such as unplanned emergency department visits and progression of chronic disease.”

Judy Cho, MD, Director of the Charles Bronfman Institute for Personalized Medicine, which runs the BioMe Biobank that houses more than 47,000 DNA and blood serum specimens from Mount Sinai’s diverse population of patients, said her team is using AI as a predictive tool. “By combining traditional clinical measures, genetics, and new blood biomarkers with AI methods, we can much more efficiently predict and treat patients earlier to try to prevent kidney failure and the need for dialysis,” Dr. Cho said. BioMe is linked to Mount Sinai’s EHRs, and enables scientists to rapidly and efficiently conduct genetic, epidemiologic, molecular, and genomic studies on large collections of research specimens linked with medical information.

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