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

Arterial Partial Pressures of Carbon Dioxide Estimation Using Non-Invasive Parameters in Mechanically Ventilated Children

Année de parution: 2020

Objective: We aim to create a predictive model capable of giving a noninvasive, immediate and reliable estimate of the arterial partial pressure of carbon dioxide (PaCO2) in mechanically ventilated children with a better reliability than its estimation from end-tidal CO2 (PetCO2) and minute ventilation volume (Vmin) evolution.

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Using machine learning models to predict oxygen saturation following ventilator support adjustment in critically ill children

Année de parution: 2019

In an intensive care units, experts in mechanical ventilation are not continuously at patient’s bedside to adjust ventilation settings and to analyze the impact of these adjustments on gas exchange. The development of clinical decision support systems analyzing patients’ data in real time offers an opportunity to fill this gap.

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Creating a High-Frequency Electronic Database in the PICU: The Perpetual Patient*

Année de parution: 2018

Our objective was to construct a prospective high-quality and high-frequency database combining patient therapeutics and clinical variables in real time, automatically fed by the information system and network architecture available through fully electronic charting in our PICU. The purpose of this article is to describe the data acquisition process from bedside to the research electronic database.

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