Blueprint to Deploying a Machine Learning Approach in the Clinical Setting

Artificial Intelligence (AI) and machine learning hold great promise for clinical and operational improvement in healthcare. However, deploying a new technology in the clinical setting can be exceptionally challenging. This can be especially true for organizations attempting to establish a machine learning-based approach to clinical care given the large quantities of standardized data, potential workflow changes, and general education required to make it successful.

This session provides a blueprint for deploying machine learning enabled technology and processes in the clinical setting. Packed with first hand insights and lessons learned from real world deployments, it offers examples of how to introduce, implement and communicate the complex concepts of a sustainable data science strategy.

Learning Objective(s):

  1. Demonstrate how to introduce machine learning to your organization

  2. Describe successes and roadblocks experienced when taking machine learning from the lab to the field

  3. Explore expert insight on communicating complex machine learning concepts in a way providers and administrators can understand

  4. Discover how to make a machine learning approach sustainable in the clinical setting

Artifical Intelliegence, Machine Learning, Data Science, Data and Analytics, Clnical & Business Intelligence, Health IT, HIMSS