Les articles du laboratoire
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Nos articles
Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning
Année de parution: 2023When dealing with clinical text classification on a small dataset recent studies have confirmed that a well-tuned multilayer perceptron outperforms other generative classifiers, including deep learning ones. To increase the performance of the neural network classifier, feature selection for the learning representation can effectively be used.
Lien vers l'articleEvaluation of the SIMULRESP: A simulation software of child and teenager cardiorespiratory physiology
Année de parution: 2023Mathematical models based on the physiology when programmed as a software can be used to teach cardiorespiratory physiology and to forecast the effect of various ventilatory support strategies. We developed a cardiorespiratory simulator for children called “SimulResp”. The purpose of this study was to evaluate the quality of SimulResp.
Lien vers l'articleClinical Decision Support System to Detect the Occurrence of Ventilator-Associated Pneumonia in Pediatric Intensive Care
Année de parution: 2023Ventilator-associated pneumonia (VAP) is a severe care-related disease. The Centers for Disease Control defined the diagnosis criteria; however, the pediatric criteria are mainly subjective and retrospective. Clinical decision support systems have recently been developed in healthcare to help the physician to be more accurate for the early detection of severe pathology
Lien vers l'articleJoint classification and segmentation for an interpretable diagnosis of acute respiratory distress syndrome from chest x-rays
Année de parution: 2023Joint classification and segmentation for an interpretable diagnosis of acute respiratory distress syndrome from chest x-rays. However, despite the extensive literature on chest x-ray (CXR) image analysis, there is limited research on ARDS diagnosis due to the scarcity of ARDS-labeled datasets. This work aims to develop a method for detecting signs of ARDS in CXR images that can be clinically interpretable.
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