The Machine Learning Marketplace is a unique 2-hour breakout that will provide attendees a broad exposure to a wide variety of innovative use cases for machine learning in healthcare. This session will be divided into two segments.
The first hour segment will consists of 12 stations providing 5-minute overviews of how they are using machine learning. The audience will be seated and able to see a broad array of use cases, and determine which of the use cases they would like to investigate further.
The second hour segment will consist of the audience walking around and conversing directly with the presenters at 12 individual stations. Each of the health systems will be available to explain more in depth about their machine learning projects, including results and key lessons learned.
Case studies in this session include using machine learning to assist in real-time inpatient care, detecting errors in medical data (comorbidities), optimizing no-show rates, determining risk modeling in falls, maintaining machine learning models after launching, predicting no-show patients, determining opioid risk, assessing readmission risks, and analyzing unstructured data, VOC data, and social media data to create actionable insights.