4 discoveries from Cedars-Sinai's AI division

The Department of Medicine at Cedars-Sinai has released some of its trailblazing AI developments that have been able to predict, diagnose and assess risk of major human disease conditions. 

The division, called Artificial Intelligence in Medicine, was launched March 1 and is led by Sumeet Chugh, MD.

Researchers access data from the Cedars-Sinai Health System's clinical data warehouse, using machine learning and deep learning methods to create its own tools and algorithms that have the potential to enhance human disease prevention.

Four innovation discoveries and developments from the division: 

  1. Researchers developed an AI algorithm that predicts which patients will develop treatable forms of heart conditions. The algorithm was able to sort through nuclear and CT scans to predict heart attack risk, analyze echocardiograms to better detect rare heart conditions and distinguish between risk of fatal and treatable sudden cardiac arrest.

  2. The research team is working to develop AI software that processes all CT scans to detect pulmonary embolism, cervical spine fracture and subtle brain bleeds. The aim of the research is to develop an AI that can flag the most dangerous and time-sensitive cases.

  3. The division is studying whether AI can be used to shorten the length of inpatient stays.
     
  4. Researchers have developed software that predicts the risk of pancreatic cancer. The software was trained to compare CT scans of patients with confirmed pancreatic cancer to scans with healthy patients. The model was able to accurately identify which patients would eventually be diagnosed with pancreatic cancer.

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