Artificial Intelligence

AI and Machine Learning Projects

AI and Machine Learning in the Surgical Innovation Center

A major focus of the center is in harnessing the massive quantities of healthcare data to develop predictive models that can be used for individualized patient care and for supporting clinical decision-making. We will also focus on developing algorithms that can accurately and in an automated fashion interpret imaging studies, and using AI/ML and natural language processing to accurately and rapidly extract data from the electronic health record.

Current Projects in Artificial Intelligence and Machine Learning

AI approaches to detecting the severity of carotid artery disease - Lead investigator: Ravi Veeraswamy, M.D. 

Machine Learning and AI approaches to risk modeling for cardiac surgery  for quality improvement - Lead investigator: Arman Kilic, M.D. 

Using AI to improve efficiency in organ allocation systems for heart transplants - Lead investigator: Arman Kilic, M.D. 

Developing AI methods to extract unstructured data from the electronic health record to automate reporting of data and quality control - Lead investigator: Arman Kilic, M.D. 

Investigating an AI algorithm for automatic detection of  surgical wound infections - Heather Evans, M.D. MS