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Progress using covid-19 patient data to train machine learning models for healthcare

3 April 2020 by Sean O'Neill

CCAIM Director, Professor Mihaela van der Schaar, demonstrates that machine learning techniques can accurately predict how covid-19 will impact hospital resource needs, such as ventilators and ICU beds at the individual patient level and the hospital level, enabling healthcare professionals to make well-informed decisions about how these scarce resources can be used to achieve the maximum benefit. She reveals a proof-of-concept demonstrator showing that this can be done.

Read the full story.

 

Category: COVID-19 News, News, Uncategorised
Previous Post: « Responding to covid-19 with AI and machine learning 
Next Post: From black boxes to white boxes »

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MihaelaVDS avatarMihaela van der Schaar@MihaelaVDS·
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I'm thrilled to unveil a project our lab has been working on for a while: a series of video tutorials on individualized treatment effect inference! Each of our 6 tutorials has its own syllabus composed of a range of different modules. Find the series here: https://www.vanderschaar-lab.com/video-tutorials-individualized-treatment-effect-inference/

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