SADC

Regroupement en IA
soins aigus pour l'enfant

Les articles du laboratoire

Le laboratoire croit en une vision basée sur un modèle d’innovation ouverte pour les membres du groupe et partiellement ouverte ou contrôlé à l’extérieur du groupe. Dans cette optique, nous souhaitons partager nos connaissances et faire rayonner le milieu académique avec la publication d'articles.

Nos articles
 

Data Representation Structure to Support Clinical Decision-Making in the Pediatric Intensive Care Unit: Interview Study and Preliminary Decision Support Interface Design

Année de parution: 2024

In this study, we designed a prototype to optimize the representation of clinical data collected from existing sources (eg, EHR, clinical systems, and devices) via a structure that supports the integration of a home-developed CDSS in the PICU. This study was based on analyzing end user needs and their clinical workflow.

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Evaluation of the SIMULRESP: A simulation software of child and teenager cardiorespiratory physiology

Année de parution: 2023

Mathematical 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.

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Clinical Decision Support System to Detect the Occurrence of Ventilator-Associated Pneumonia in Pediatric Intensive Care

Année de parution: 2023

Ventilator-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

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Situation Awareness-Oriented Dashboard in ICUs in Support of Resource Management in Time of Pandemics

Année de parution: 2023

In a pediatric intensive care unit (PICU) of 32 beds, clinicians manage resources 24 hours a day, 7 days a week, from a large-screen dashboard implemented in 2017. This resource management dashboard efficiently replaces the handwriting information displayed on a whiteboard, offering a synthetic view of the bed’s layout and specific information on staff and equipment at bedside. However, in 2020 when COVID-19 hit, the resource management dashboard showed several limitations.

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Joint classification and segmentation for an interpretable diagnosis of acute respiratory distress syndrome from chest x-rays

Année de parution: 2023

Joint 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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Hemodynamic assessment in children after cardiac surgery: A pilot study on the value of infrared thermography

Année de parution: 2023

Low cardiac output syndrome in the postoperative period after cardiac surgery leads to an increase in tissue oxygen extraction, assessed by the oxygen extraction ratio. Measurement of the oxygen extraction ratio requires blood gases to be taken. However, the temperature of the skin and various parts of the body is a direct result of blood flow distribution and can be monitored using infrared thermography. Thus, we conducted a prospective clinical study to evaluate the correlation between the thermal gradient obtained by infrared thermography and the oxygen extraction ratio in children at risk for low cardiac output after cardiac surgery.

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Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning

Année de parution: 2023

When 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.

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Multimodality Video Acquisition System for the Assessment of Vital Distress in Children

Année de parution: 2023

In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting.

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