Machine Learning
Predictive Monitoring: IMPact of Real-Time Predictive Monitoring in Acute Care Cardiology Trial (PM-IMPACCT)
This research evaluates an artificial intelligence risk predictive tool called CoMET that uses visual outputs of patient data to serve as an early warning system for patients at risk of cardiac decompensation to allow for earlier intervention and reduction in morbidity and mortality.
Harnessing Health Information Technology to Promote Equitable Care for Patients with Limited English Proficiency and Complex Care Needs
This research will test and validate a machine learning predictive analytic intervention to optimize the timely and appropriate use of interpreters for hospitalized patients with language barriers and complex care needs.
Improving Health Data Quality by Assessing and Enhancing Semantic Integrity
This research will develop and validate advanced statistical and machine learning methods to assess and improve representational semantic integrity of terminologies in large clinical databases.