This solution participated in a Driver+ Trial


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AIR is a Deep Neural Network (DNN) model used for predicting the excess mortality due to antimicrobial resistance. Additionally, it incorporates patient’s contextual epidemiological and infectious information.

Antimicrobial Resistance Model is a predictive model that once developed will predict the excess mortality rate of one of the five pathogens (ESBL E.coli) examined within the STAMINA project. AIR model relies on Multi-Task Learning (MTL) implemented with Deep Neural Networks with shared hidden layers and is applied to predict excess mortality due to antimicrobial resistance. Among the model’s goals, reducing the medical treatment’s economic burden, as well as improving the patient’s overall quality of life, are included.

Supported Use Cases

Predict E.coli excess mortality

Predict the excess mortality rate of ESBL E.coli due to antimicrobial resistance. 

Related CM functions

AIR models architecture (both Single Task Learning and Multi-Task Learning)
eu Portfolio of Solutions web site has been initially developed in the scope of DRIVER+ project. Today, the service is managed by AIT Austrian Institute of Technology GmbH., for the benefit of the European Management. PoS is endorsed and supported by the Disaster Competence Network Austria (DCNA) as well as by the STAMINA and TeamAware H2020 projects.