2 citations · 2 across the 3 of their papers we have counts for
3 papers
To Recommend or Not to Recommend: Designing and Evaluating AI-Enabled Decision Support for Time-Critical Medical Events
Angela Mastrianni, Mary Suhyun Kim, Travis M. Sullivan +4
AI-enabled decision-support systems aim to help medical providers rapidly make decisions with limited information during medical emergencies. A critical challenge in developing the…
Exploring Runtime Decision Support for Trauma Resuscitation
Keyi Li, Sen Yang, Travis M. Sullivan +2
AI-based recommender systems have been successfully applied in many domains (e.g., e-commerce, feeds ranking). Medical experts believe that incorporating such methods into a clinic…
Generating Privacy-Preserving Process Data with Deep Generative Models
Keyi Li, Sen Yang, Travis M. Sullivan +2
Process data with confidential information cannot be shared directly in public, which hinders the research in process data mining and analytics. Data encryption methods have been s…