Machine Learning

Optimal acute kidney injury algorithm for detecting acute kidney injury at emergency department presentation.

Principal Investigator

Predictive Monitoring: IMPact of Real-Time Predictive Monitoring in Acute Care Cardiology Trial (PM-IMPACCT)

Description

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.

Grant Number
R01 HS028803

Incorporating patient-reported outcomes into shared decision-making in the management of patients with osteoarthritis of the knee: a hybrid effectiveness-implementation study protocol.

Principal Investigator

Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events.

Principal Investigator

Responding to health information technology reported safety events: Insights from patient safety event reports.

Principal Investigator

A machine learning approach to reclassifying miscellaneous patient safety event reports.

Principal Investigator

Advancing motivational interviewing training with artificial intelligence: ReadMI.

Principal Investigator