Using AI to Improve Clinical Outcomes
Clinical Data Science
We are a team of data scientists and engineers that leverage the power of ML and AI at Mount Sinai Hospital.
Clinical Conditions
Data science, machine learning (ML) and artificial intelligence (AI) have the potential to transform the delivery of clinical care and improve early recognition and diagnosis of clinical conditions
Hospital Operations
AI allows us to gain new insights and continuously improve over time as the platform learns from our patients and clinicians to enhance hospital operations
Awareness and Intervention
We have built a powerful real-time streaming clinical data platform that brings the power of ML and AI to improve provider awareness and timely intervention
Mount Sinai Ranks as No. 1 Health Care Institution according to Nature AI Index
Mount Sinai Health System has been ranked No. 1 on the new Nature AI Index 2024 of leading healthcare institutions. Here's full press release from Mount Sinai Communications: Mount Sinai Health System is No. 1 on the new Nature AI Index 2024 list of “Leading 10...
Mount Sinai ranked among the top 10 smart hospitals in the world
Mount Sinai has once again been ranked among the top 10 smart hospitals in the world by Newsweek: This recognition is a direct result of our collective commitment to advancing healthcare through digital, AI, data, and informatics. Robbie Freeman,Vice President of...
Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial*
The "Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial*" paper, which was authored by several members of the Clinical Data Science team, has been published in the Critical Care Medicine journal, July...
Mount Sinai Health System named 2024 Hearst Health Prize winner
The Clinical Data Science team at Mount Sinai Hospital was named the winner of the 2024 Hearst Health Prize. The team was declared the winner for its malnutrition identification machine learning engine, which is used to better identify patients with malnutrition...
Mount Sinai’s CDS team nominated for the Hearst Health Prize
Mount Sinai's Clinical Data Science team has been nominated for the Hearst Health Prize! "The Hearst Health Prize showcases data science programs making an impact on human health. The judges evaluated submissions using several criteria, including demonstrated health...
Next-Generation Health Care: AI-Driven Patient Risk Profiling for Pressure Injuries in The Mount Sinai Hospital
CDS' Hospital Acquired Pressure Injury Prevention project has been featured in Mount Sinai's Spring 2024 nursing newsletter, Magnet NEWS. The full article can be found on pages 20-21 (https://mshs.co/3UN8hIS).
“Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial” study published in Critical Care Medicine journal
The study titled "Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial", authored by Dr. Levin and several members of the Clinical Data Science team, has been published in the Critical Care Medicine...
CDS presentation in the 2024 Critical Care Congress
The Clinical Data Science team, represented by our data scientist Kim-Anh-Nhi Nguyen, MSc, presented the paper "A Deep Learning Model using Chest X-Rays to Predict Re-Intubation Risk in Critical Care" at the 2024 Critical Care Congress in Phoenix, Arizona. More...
A Hybrid Decision Tree and Deep Learning Approach Combining Medical Imaging and Electronic Medical Records to Predict Intubation Among Hospitalized Patients With COVID-19: Algorithm Development and Validation
A new paper written by the Clinical Data Science team has been published in JMIR (https://formative.jmir.org/2023/1/e46905). Background: Early prediction of the need for invasive mechanical ventilation (IMV) in patients hospitalized with COVID-19 symptoms can help in...