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Alejo Jumat

Alejo is a User Experience Design professional with over 16 years of experience ensuring software is both usable and useful for end-users. He solves complex problems in Healthcare through Design and believes that great Design (that is grounded in human factors and human-centered research)can improve the state of Healthcare IT. His focus has been turning complex workflows into easy-to-use web & mobile applications that help people get their job done in an efficient and safe way. Alejo earned a BBA with a focus in Information Systems from George Washington University and an M.S. in Information Systems Technology from George Washington University. He is also a Certified Usability Analyst through Human Factors International.

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Valere Lemon, MBA, RN
Alejo Jumat

Meaningful Machine Learning Visualizations for Clinical Users: A Framework

Health systems can leverage the predictive potential of machine learning to improve outcomes, lower costs, and save lives. Machine learning, however, doesn’t inherently produce insights that are actionable in the clinical setting, and frontline clinicians need information that’s accessible and meaningful at the point of care. Thoughtfully designed visualizations of machine learning insights are a powerful way to give clinical users the information they need, when and how they need it, to support informed decision making.
A design framework for machine learning visualizations addresses three key questions about who will use the decision-support insights and how:

People: who are the targeted users?
Context: in what context or environment do they work?
Activities: what activities do they perform?

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