Collaboration between CHUV, SDSC and UNIL

Thanks to a collaboration between CHUV, EPFL – through the Swiss Data Science Center – and UNIL, a predictive platform based on artificial intelligence is under development to improve patient care.
By
Swiss Data Science Center
June 27, 2024
Share this post

The first prototypes of applications for predicting the risk of bedsores and recognizing sepsis already show very promising results. This platform would, for example, increase the prediction of bedsores risk by 15 to 20% in hospitalized elderly patients at CHUV and support healthcare teams in implementing preventive measures in real time.

 

View the video for more details about the project (version française): https://www.youtube.com/watch?v=tYYfvzqvmeA

About the author

Share this post

More blog posts

March 12, 2025

First National Calls: 50 selected projects to start in 2025

First National Calls: 50 selected projects to start in 2025

50 proposals were selected through the review processes of the SDSC's first National Calls.
Blog
January 22, 2025

AIXD | Generative AI toolbox for architects and engineers

AIXD | Generative AI toolbox for architects and engineers

Introducing AIXD (AI-eXtended Design), a toolbox for forward and inverse modeling for exhaustive design exploration.
Blog

More news

June 29, 2017

Open and reproducible environmental science: from theory to equations and algorithms

Open and reproducible environmental science: from theory to equations and algorithms

We need complex models that accurately represent the feedbacks between different processes and compartments to inform us how a perturbation in one component may affect other components of the coupled climate-earth surface system that are relevant to us.
Blog
October 28, 2021

DEAPSnow | Supporting avalanche forecasting in the Swiss Alps using machine learning

DEAPSnow | Supporting avalanche forecasting in the Swiss Alps using machine learning

The creation of avalanche bulletins is still a largely expert-driven and manual task. DEAPSnow aims to explore the feasibility of using data-driven models to support the process of avalanche danger forecast.
Blog

Contact us

Let’s talk Data Science

Do you need our services or expertise?
Contact us for your next Data Science project!