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AI vs COVID-19: How Java helps nurses and doctors in this fight

June 9, 2020
Geoffrey De Smet Edson Yanaga
Related topics:
Event-DrivenJavaQuarkus
Related products:
Red Hat build of OpenJDKRed Hat build of QuarkusRed Hat JBoss Enterprise Application Platform

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    DevNation Tech Talks are hosted by the Red Hat technologists who create our products. These sessions include real solutions plus code and sample projects to help you get started. In this talk, you’ll learn how OptaPlanner has helped keep medical staff and patients safer with advanced planning algorithms, from Geoffrey De Smet and Edson Yanaga.

    Assigning nurses and doctors to hospital shifts is far more challenging than it looks on the surface. Don’t give two shifts at the same time. Adhere to skill requirements. When going home, leave enough time for a full night’s sleep. Maximize approval of their day off requests. Make the schedule fair. With advanced planning algorithms, the best-kept secret in AI, you can solve this challenge easily in Java.

    Advanced planning algorithms can do better than human planning, in far less time. OptaPlanner is used across the globe for such use cases. In this session, I’ll show you how. Then a pandemic hits—time for some business agility. Don’t put diabetic nurses in COVID wards. Avoid putting a non-COVID shift after a COVID shift. When enough nurses recover from the virus, distribute them such that each ward has an inoculated nurse at all times. Fortunately, we can add such constraints in OptaPlanner quickly.

    Watch the entire talk:

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    Join us at an upcoming developer event, and see our collection of past DevNation Tech Talks.

    Last updated: February 11, 2024

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