Science and technology have created tremendous opportunities to improve and extend our lives. At the Hasso Plattner Institute for Digital Health at Mount Sinai, we use the tools of data science, biomedical and digital engineering, and medical expertise to advance health care. The institute is a collaboration between the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany, and the Mount Sinai Health System. Our goal is to develop innovations to revolutionize how people think about their personal health and health systems and have a tangible impact on patients’ lives.
The institute strives to develop research projects and artificial intelligence technologies to improve our ability to diagnose and treat patients. The Hasso Plattner Institute for Digital Health at Mount Sinai receives generous support from the Hasso Plattner Foundation. Below, we outline our research projects and machine learning efforts.
At the institute, we perform research that combines biomedical and data sciences to develop digital health solutions for both patients and researchers. Our research projects include:
- Digital Discovery Program: The Digital Discovery Program (DDP) is a comprehensive program of patient-centric health studies and clinical tools utilizing wearable, mobile and sensor technologies to generate and integrate multi-modal data to better understand these complex diseases which impact millions of individuals, lead to loss of life and health and costs billions each year.
- AI Ready Mount Sinai Platform: This multi-modal health data platform links patient data generated from different clinical departments to mitigate siloing and accelerate the advancement of health-care-driven, artificial intelligence (AI)-based solutions.
Machine Learning Efforts
Machine learning is a type of artificial intelligence research that enables a computer to use learning algorithms to draw inferences from data and “learn” new skills. These projects are intended to improve our provision of health care diagnostics and treatments. Projects include:
- FlexIBle EHR Retrieval (FIBER): Using clinical data from a series of electronic libraries, this project streamlines the clinical modeling process.
- Natural-Language Processing on Clinical Notes for Phenotyping Depression: This software application provides insights into patients’ underlying biological or neurological mechanisms that can inform and improve treatment decisions.
- Prediction of Hypertension Onset by Leveraging EHR Data with Machine Learning: This system uses several machine learning approaches to help predict whether a patient will develop hypertension, facilitating early intervention.
- Process Mining in Personalized Medicine: This technology analyzes real-world business process management problems to improve data flow and patient outcomes.
Meet Our Team
The Hasso Plattner Institute at Mount Sinai is a research and education hub dedicated to bringing together faculty, research staff, and students from the Icahn School of Medicine at Mount Sinai and the Hasso Plattner Institute for Digital Engineering.
Erwin P. Bottinger, MD, Co-Director
Erwin Bottinger is the Co-Director of the Hasso Plattner Institute for Digital Health at Mount Sinai and Head of the Digital Health Center at the Hasso Plattner Institute in Potsdam, Germany. He holds dual academic appointments as Professor of Medicine, and Systems Pharmacology and Therapeutics, at the Icahn School of Medicine at Mount Sinai, and chaired Professor for Digital Health - Personalized Medicine at the joint Digital Engineering Faculty of the HPI and University Potsdam. From November 2015 to July 2017 Dr. Bottinger was the CEO of the Berlin Institute of Health, where he played a key role in shaping its strategy for “Personalized Medicine - Advanced Therapies.” From 2007 to 2015, he served as Founding Director of the Charles Bronfman Institute for Personalized Medicine at the Icahn School of Medicine and principal architect of the Institute’s BioMe™ Biobank. Dr. Bottinger is a pioneer in groundbreaking implementations of personalized medicine and digital health in clinical practice.
Thomas J. Fuchs, DSc, Co-Director
Thomas J. Fuchs, DSc, is a scientist in the groundbreaking field of Computational Pathology, focused on the use of artificial intelligence to analyze images of tissue samples to identify disease, recommend treatment and predict outcome. In October 2020, he has been appointed Co-Director of the Hasso Plattner Institute for Digital Health at Mount Sinai, Dean of Artificial Intelligence (AI) and Human Health, and Professor of Computational Pathology and Computer Science at the Icahn School of Medicine at Mount Sinai. Before joining Mount Sinai, Dr. Fuchs was Director of the Warren Alpert Center for Digital and Computational Pathology at Memorial Sloan Kettering Cancer Center (MSK) and Associate Professor at Weill Cornell Graduate School for Medical Sciences. At MSK he led a laboratory focused on computational pathology and medical machine learning. Dr. Fuchs co-founded Paige.AI in 2017 and led its initial growth to the leading AI company in pathology. He is a former research technologist at NASA’s Jet Propulsion Laboratory and visiting scientist at the California Institute of Technology. Dr. Fuchs holds a Doctor of Sciences from ETH Zurich in Machine Learning and a MS in Technical Mathematics from Graz Technical University in Austria.
Girish N Nadkarni, MD, Clinical Director Hasso Plattner Institute at Mount Sinai / Assistant Professor of Medicine, Nephrology, Icahn School of Medicine at Mount Sinai
Benjamin Glicksberg, PhD, Assistant Professor of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai
Christoph Lippert, PhD, Chair of Digital Health and Machine Learning, Hasso Plattner Institute