Division of Data-Driven and Digital Medicine (D3M)

MEDICINE

Division of Data-Driven and Digital Medicine (D3M)

At a time when every medical decision, every diagnosis, and every treatment is underpinned by data, the Division of Data-Driven and Digital Medicine (D3M) is a leap toward a future where artificial intelligence and digital tools are not simply integrated into—but become intrinsic to—clinical practice.

Situated within the Icahn School of Medicine at Mount Sinai, the Division has as its mission bringing data-driven and digital innovation to research, education, and clinical care, thereby empowering each to reach its maximum new potential.

Modern medicine’s transformative new era is fueled by data science, artificial intelligence (AI), and digital health. At the Division of Data-Driven and Digital Medicine, we aim to be the epicenter of that transformation, catalyzing groundbreaking research, training the next generation of physicians, and ensuring a seamless translation of digital innovation into clinical practice.

We recognize that through education we can ensure our future biomedical leaders are pioneers in this new era of medicine, rather than just participants. We are committed to training medical students, residents, and fellows, by introducing them to the possibilities of AI, data science, and digital health innovation. Our collaboration with several key Mount Sinai entities additionally ensures that our vision is not confined to a single department but shared across the entire Mount Sinai Health System.

Data science can now illuminate every turn in a patient’s path, guiding clinical experiments that shape the very essence of our practice. Yet like any pioneering journey, we face challenges. If left unaddressed, these challenges hinder the realization of a future where precision medicine is not just a concept, but a daily reality that radically advances patient care.

Recognizing the pivotal role of data in sculpting this future, the Icahn School of Medicine at Mount Sinai created the Division of Data-Driven and Digital Medicine in 2022. D3M is Icahn Mount Sinai’s commitment to that future where we harness the full potential of data-driven medicine and AI to enhance patient care, where we prepare the next generation of physicians for a new era of health care, and where every piece of information becomes a tool to heal, to understand, and to innovate.

We invite you to join us as we step into a future fully illuminated by data, where precision, compassion, and innovation remain central to our ongoing mission.

Girish Nadkarni, MD, MPH
Chief, Data Driven and Digital Medicine
Director, The Charles Bronfman Institute of Personalized Medicine
Irene and Dr. Arthur Fishberg Professor of Medicine

D3M catalyzes research and decreases barriers for clinicians and scientists seeking to use data to improve clinical decision-making and patient outcomes.

Our faculty members mentor those interested in exploring the intersection of medicine and artificial intelligence, and our trainees have won numerous accolades, including the Sinai Trainee Innovation Award and career development awards from the Clinical and Translational Institute.

Our current innovation investigations focus on:

Using multi-modal data to understand genetic, clinical, and social determinants of disease.

We combine data from multiple different sources, such as genetic information, imaging, and medical records information, to create models that can help us predict who will develop a certain disease or will experience a worsening of their disease.
We also use novel methods to identify patients with unmet social determinants of health and incorporate these determinants to improve model performance.

Developing novel methods to analyze and harness multi-modal data.

We have developed novel Deep Learning (DL) techniques, including embeddings and novel network architectures, on a variety of waveform and electronic health record data to improve model performance or predict novel endpoints.
We have also created new methods to improve explanations of machine learning approaches and developed and applied causal machine learning methods to understand and address modifiable risk factors in machine learning models.

Predicting the incidence and progression of disease.

We have constructed novel prediction models that have high accuracy for predicting incidence and progression of various diseases, including acute kidney injury and chronic kidney disease.
We have also created novel methods to include non-traditional risk factors into prediction models, which have resulted in improved performance over traditionally used clinical models.

At the Division of Data-Driven and Digital Medicine, our Artificial Intelligence/Machine Learning analyst group consists of dedicated analysts who have access to multi-modal data across Mount Sinai Health System, as well as external databases.

These analysts help clinicians and investigators execute relevant projects. Our collaboration with the Clinical Data Science team, led by Robert Freeman RN, MSN, NE-BC, helps us then translate relevant data-driven approaches into clinical care. Our recent projects include generating preliminary data for grants submissions, pulling clinical data for research purposes, and identifying cohorts of patients for clinical research.