Title of the research project
Study of bacterial-phage interactions in in vitro gut digestion systems
Description

Rose-Marie's project focuses on the analysis of interactions between bacteriophages - the viruses of bacteria - and bacteria of the intestinal microbiota based on datasets from experiments carried out by the student in collaboration with members of the Institute of Nutrition and Functional Foods (INAF) at Université Laval. The first objective is to study the impact of phages on bacterial dynamics in a simplified microbiota, composed of 8 key bacterial strains of the human intestinal microbiota.

Title of the research project
Study of bacterial-phage interactions in the intestinal microbiota of the general population of Quebec
Description

Alexandre Boulay's project involves the analysis of phages and bacteria in the gut microbiota from a metagenomic dataset from the Institute of Nutrition and Functional Foods (INAF) at Université Laval, relying on bioinformatics and artificial intelligence (AI) methods. The dataset comes from a recent study that examined the interaction of the endocannabinoid axis with host environmental factors as well as gut, metabolic and mental health status in Quebec adults with various metabolic and lifestyle statuses.

Title of the research project
Conversion of HDF5 Segmentation Files to DICOM
Description

The intern developed a tool for converting pulmonary nodule annotation data stored inHDF5 files to theDICOMfile format. The tool enables the extraction of annotation data from the HDF5 file as well as the lung computed tomography (CT) data of patients stored in a database. Subsequently, the tool generates and saves a DICOM annotation file following the structure indicated by the DICOM Standard Browser. The student programmed this tool in Python while keeping track of versions using Gitlab.

  • Elsa Rousseau

    Assistant Professor
    Faculté des sciences et de génie
    Université Laval

    Elsa Rousseau est professeure adjointe au Département d’informatique et de génie logiciel de la Faculté des sciences et de génie à Université Laval, et au sein du Centre NUTRISS-Nutrition, santé et société. Son programme de recherche porte sur l’étude des interrelations entre le microbiote, les bactériophages et la nutrition, via l’élaboration d’approches en intelligence artificielle pour déterminer leurs impacts sur la santé cardiométabolique.


    Elsa a obtenu son diplôme d’ingénieure en bio-informatique et modélisation à l'INSA Lyon en 2011, puis son doctorat de l’université de Nice Sophia Antipolis en 2016, en modélisation de l’épidémiologie et de l’évolution des virus. Elle a ensuite réalisé deux postdoctorats, un premier chez IBM, dans leur réputé Centre de recherche Almaden à San Jose (CA), en modélisation mathématique des dynamiques de populations virales pour l’élaboration d’un nouveau type de traitement, puis un second dans le laboratoire de Jacques Corbeil au Centre de recherche du CHU de Québec-Université Laval, en codirection avec François Laviolette, en bio-informatique et intelligence artificielle pour l’analyse de données métagénomique en santé.


    Elsa est membre régulière du Centre de recherche en données massives de l'Université Laval (CRDM), de l’Institut intelligence et données (IID), de l’Institut sur la nutrition et les aliments fonctionnels (INAF), et membre associée à l’Observatoire international sur les impacts sociétaux de l’IA et du numérique (OBVIA).
     

  • Title of the research project
    Detection of delirium using physiological parameters and hypovigilance monitoring: a pilot observational cohort study
    Description

    Delirium is a condition that, when left unmanaged, is associated with increased mortality and longer hospitalization of patients in intensive care; therefore, its detection should be an integral part of care. It is characterized by confusion, anxiety and reduced alertness. It is estimated that 75% of delirium cases are not detected on admission to hospital. Detecting such an acute condition requires frequent monitoring of participants, which is labor intensive and requires expertise.

    Title of the research project
    Development of GPU-based optimization algorithms for treatment planning in HDR brachytherapy
    Description

    High-dose-rate (HDR) brachytherapy is a standard treatment modality to treat cancer (e.g., prostate and cervical cancer) using the ionizing radiation of a small encapsulated radioactive source. The curative aim in the clinic is to create treatment plans that maximize the dose to the tumor while minimizing the dose to normal tissues. When it comes to the treatment plan generation, manual fine tuning of an objective function is necessary to achieve optimal trade-offs between these two conflicting objectives.

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    Featured project

    This research project is based on the analysis of massive data on the NOL index and other intraoperative clinical parameters used by anesthesiologists during surgery. These parameters help them make analgesic treatment decisions in a non-communicating patient under general anesthesia and in whom it is impossible to assess pain and analgesic needs by standard questionnaires performed on awake patients. 
    First, the objective is to interpret the values of this index in relation to the decisions made by the clinician. 

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