The Mount Sinai Health System has been an early adopter of artificial intelligence (AI) in improving patient care and health over the past few years, innovating in various clinical areas such as in imaging and patient monitoring. Now, the Health System is doubling on its investment in the field, and is opening the Hamilton and Amabel James Center for Artificial Intelligence and Human Health on November 25, a 12-story, 65,000-square-foot facility at 3 East 101st Street. The facility aims to organize Mount Sinai’s artificial intelligence (AI) efforts under one roof, to facilitate collaboration and innovation.
“Mount Sinai sees artificial intelligence and machine learning as key to our continued successes in making critical discoveries in science and in advancing medicine,” says David Reich, MD, President of The Mount Sinai Hospital.
The co-location of data scientists with the basic science and clinical scientists on the campus shared by the Icahn School of Medicine at Mount Sinai and The Mount Sinai Hospital is a strategic decision to create a community of clinical, basic, and data scientists that interact seamlessly.
The new building houses Mount Sinai’s core AI facilities: the Windreich Department of Artificial Intelligence and Human Health; the Hasso Plattner Institute for Digital Health at Mount Sinai; the Institute for Genomic Health; the Mount Sinai BioMedical Engineering and Imaging Institute; and the Charles Bronfman Institute for Personalized Medicine.
Exterior of the Hamilton and Amabel James Center for Artificial Intelligence and Human Health.
Investing in AI is key to Mount Sinai’s commitment to patient health. “Science and medicine are advancing rapidly and artificial intelligence is the key to scaling our ability to help our staff be more effective in creating better outcomes and enhancing safety in multiple clinical domains and to speed scientific discovery,” says Dr. Reich.
What do the core facilities do, and what are some of the research activities going on inside? Click on each button to find out more.
The Department was founded more than two years ago. Its inaugural Chair, Thomas Fuchs, Dr.sc., Dean for Artificial Intelligence, set a goal of designing an “intelligent fabric”—a platform containing various AI tools and services that can be easily integrated into clinical applications at hospitals within the Health System. This centralized platform would help clinicians get a holistic view of the patient, which not only helps on the diagnostic side, but also for treatment decisions, better follow-up, and better prevention of disease, says Dr. Fuchs.
The Department has more than 80 faculty members, spanning clinicians, basic scientists, computer scientists, and engineers. In addition to creating AI tools for the Health System, it hosts the annual New Wave of AI in Healthcare conference to share findings with Mount Sinai researchers and other institutions around the country. Research areas include computational pathology and machine learning in chronic disease characterization and management. Some activities include:
- Oncology: In collaboration with The Tisch Cancer Institute, an ongoing project involves the development of computational biomarkers for cancer, which could be used to predict patient outcomes and recommend treatment options or clinical trials for patients.
- Neurology: The Department is involved in the 10,000 Brains Project, a philanthropic initiative that uses AI in the fight against neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. It intends to digitize neuropathology slides of brains across diverse populations, aiming to uncover underlying mechanisms and shed light on diagnostic and treatment options in the future.
- Pathology: Team members are building what could be considered the largest academic foundation model in pathology. It comprises billions of images from millions of digitized slides to provide data and information about the microscopic world. This data could be used as a foundation for AI applications to build biomarkers, create predictive models, or answer questions about cancer and tissues.
Learn more about the Windreich Department of Artificial Intelligence and Human Health
- AI-Ready Mount Sinai (AIR·MS): Patient data, such as scans or clinical reports, can often be siloed in separate departments. AIR·MS is a cloud-based platform that integrates Mount Sinai patient data into a consistent format. This platform allows researchers access to information about Mount Sinai’s 12 million patients to build out AI applications at scale or to conduct research.
- Ehive: A platform involving a mobile application, available on the Apple App Store or Google Play, that conducts digital health studies. Participants answer questions on the app and provide other health information via wearables, such as an Apple Watch, for the study’s duration. Ehive helps researchers understand complex diseases and wellness.
Learn more about the Hasso Plattner Institute for Digital Health at Mount Sinai
- Genomic discovery: Teams are involved in large-scale projects that infer population history through genetic sequencing. These studies provide information about how genetic diversity has changed throughout history, evolution, and disease. Ongoing projects vary in scope from the local population in East Harlem in Manhattan to continental populations in North and South America.
- Medical genomics: With a better understanding of genetic data, researchers can infer the prevalence, clinical impact, and comorbidities associated with a particular variant. The institute is involved in the NYCKidSeq clinical trial, a collaboration between Mount Sinai, the New York Genome Center, and Montefiore Medical Center and its Albert Einstein College of Medicine, to find genetic causes of health problems in children. Other efforts look at the intersection of genomics and infectious diseases, screening, and electronic health records.
With a team of more than 45 members and under the leadership of its Director, Zahi Fayad, PhD, the Institute works at the forefront of imaging, nanomedicine, and drug delivery, with a focus on brain, heart, and cancer research. The Institute has a track record with wearable innovations, but it is also making strides in AI-powered digital solutions. Some recent innovations include:
- Warrior Watch: By applying AI to analyze heart rate and other variables collected via an Apple Watch, researchers developed a way to monitor and assess psychological states remotely without requiring the completion of mental health questionnaires. The study found the AI model to be predictive in identifying resilience or well-being states.
- “Digital twin”: By computationally modeling pathway interactions of cells and organs, researchers at the institute have created essentially a “digital twin” of organs. This allows researchers to make predictions about gene expression and organ function, which in turn allow for better understanding of health and disease states.
Learn more about the Mount Sinai BioMedical Engineering and Imaging Institute
Spearheading the biobank programs, including the BioMe® and Mount Sinai Million Health Discovery programs, the Institute, guided by co-Directors Alexander Charney, MD, PhD, and Girish Nadkarni, MD, works closely with the Institute for Genomic Health and others to understand human disease through cohort studies. AI is the backbone for genetic sequencing to provide insight into how one’s genes might influence health, but also other factors including environmental and socioeconomic.
- Mount Sinai Million Health Discoveries Program: This endeavor aims to carry out genetic sequencing of 1 million Mount Sinai patients in five years, and is considered one of the largest sequencing projects of its kind. With understanding of health at a local and population level, the program hopes not only to discover new therapeutics to treat and prevent disease, but also to integrate genomic profiling into routine clinical decision-making.
- BioMe®: A vast, ongoing collection of de-identified data comprising information about DNA, plasma, clinical medical records, and questionnaire data, and large-scale genome-wide genotype and exome-chip data. Since its creation in 2019, the biobank has acquired information from more than 52,500 patients. The database allows genetic, epidemiologic, molecular, and genomic studies in many different fields, including inflammatory bowel disease, chronic kidney disease, cancer, allergic conditions, and more.
Learn more about The Charles Bronfman Institute for Personalized Medicine