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Abstract Sphere

Laboratory
Project

​At CHU Ste-Justine, the laboratory for the development and validation of decision support systems for children requiring acute care is mainly financed by public funds obtained from granting organizations.

Our Projects

We create and innovate in the healthcare sector. Here are our 6 current projects:

​1- Video diagnosis of children suffering from respiratory failure

​This project began in 2016 and is at TRL 4 with a hardware component which includes a Kinect Azur 3D camera, a Lepton 3.5 infrared camera, a Jetson card and calibrated support (camera synchronization, see figure opposite) and an algorithmic component for measuring tidal volume, respiratory rate and clinical signs of retraction.

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2- Multimodal database in seriously ill children

​Intensive care units (ICU) care for patients in life-threatening situations but encounter three main obstacles to overcome: (1) delays in detecting and managing life-threatening distress, (2) delays in implementation of good practices, (3) the lack of research tools to conduct pragmatic clinical trials integrated into ICUs.

​3- Early diagnosis of Childhood Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) affects 6 to 10% of patients admitted to intensive care annually, is currently underdiagnosed and has a mortality of 18 to 45%. We held an international consensus conference on ARDS which recommended improving the number and early diagnosis

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4- Optimization of intensive care service management

​In hospital settings, intensive care staff work under pressure and often have inadequate tools to manage intensive care unit resources

​5- OptiBrain: Clinical decision support tool for severe head trauma in children

​In 2003, the Brain Trauma Foundation proposed the first guidelines to guide the therapeutic approach for severe head trauma. Since then, several updates have been made, the most recent of which dates from 2019.

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6- VIMY Multi system

The research program seeks to use artificial intelligence for casualty management in disasters, such as chemical, biological, radiological, nuclear and explosives attacks. Vimy is a field-deployable multi-intensive care system capable of managing large numbers of casualties. It is based on an artificial intelligence capability consisting mainly of sensors, data acquisition systems, automated interactive systems and algorithms that assist in decision-making and machine learning.

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