Davide Placido
Multimodal physiological time series analysis for outcome prediction in the intensive care unit.
Rel. Filippo Molinari. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2019
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Abstract
The intensive care unit (ICU) is a hospital department where critical patients are monitored and healed: the sensors used to check their vital conditions produce a huge amount of data that can be exploited to predict outcome about their future conditions. In this work mortality prediction is performed using data recorded from more than 9000 patients in different hospitals of the Capital Region of Denmark from 2009 and 2016. Since the high number of physiological variables acquired in the ICU a study of which variables subset provides more information is carried on, taking into account the number of patients who have that subset of physiological variables monitored.
Both signal processing and statistic methods are used to extract information from the first 24 hours after the admission in the ICU; then a long short term memory (LSTM) model is used for classification and regression tasks
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