What is it about?
This paper aims to explore the feasibility of interpretable machine learning models to predict mortality in critically-ill patients suffering from stroke. To do so, a vast variety of clinical and laboratory information stored in the electronic health record, are pre-processed to allow taking into account the temporal characteristics of a patient’s stay.
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Why is it important?
Machine Learning models trained on multidimensional data can help towards decision making and correctly rapid clinical decisions can significantly contribute to the quality services provided by hospitals.
Perspectives
Our vision is to create products and services that will improve people's lives.
PhD candidate Dimitrios Dimopoulos
University of the Aegean
Read the Original
This page is a summary of: Mortality Prediction in ICU Patients Suffering from Stroke, September 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3549737.3549798.
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