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

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 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...

Big Data and AI Forum 2023-05-09

Big Data and AI Forum 2023-05-09

The Department of Technology Partners (DTP) at Mount Sinai hosts a Big Data and AI Forum periodically. The latest event took place on May 9th, 2023 and covered a host of new machine learning projects, including: Hospital Acquired Pressure Injury Risk Predictions...

Aggression Risk Score

Aggression Risk Score

The Aggression Risk Score is a prognostic tool used to identify patients with high risk of developing aggression episode during their hospital LOS, therefore helping to shift the practice towards preventive paradigms, improving patient safety, and minimizing cost of...