• Guillaume Jorandon

    Ph.D. candidate
    Faculté des études supérieures et postdoctorales
    Université Laval

    Student
    Directeur.e(s) de recherche
    Philippe Després
    Guillaume Latzko-Toth
    Start date
    Title of the research project
    Pseudo-medicine and data science: impact study of learning algorithms in the propagation of misinformation in health field
    Description

    This project studies the consequences of artificial intelligence (AI) systems and data science on public discourse, as well as their usage by the new content providers on the Web. 
    It will tackle the ethical aspects of learning algorithms and recommendation filters implemented by internet companies to select and present content to the user. Specifically, the project investigates the consequences of such algorithms on public health, especially in the propagation of medical misinformation and pseudo-medicine.

    This project aims at taking a critical oversight on data science techniques and their use. Various knowledge from different fields of humanities and social science will be applied (ethics, communication studies, philosophy of techniques) and will guide the development of technical solutions, as well as recommendations for the implementation of ethical and sustainable AI. 
    For this reason, we will need both technical and philosophical research, working towards interdisciplinary integration.
     

    • Title of the research project
    Pseudo-medicine and data science: impact study of learning algorithms in the propagation of misinformation in health field
    Description

    This project studies the consequences of artificial intelligence (AI) systems and data science on public discourse, as well as their usage by the new content providers on the Web. 
    It will tackle the ethical aspects of learning algorithms and recommendation filters implemented by internet companies to select and present content to the user. Specifically, the project investigates the consequences of such algorithms on public health, especially in the propagation of medical misinformation and pseudo-medicine.

    Title of the research project
    Geometry-based quality control for external radiation therapy planning using stochastic frontier analysis
    Description

    This project focuses on the use of machine learning techniques in external radiotherapy for cancer treatment planning.
    Stochastic frontier analysis is a parametric approach used in econometrics and appropriated for medical physics. Using a retrospective bank of treated patients it will be possible to predict the optimal dose of radiation for tumor and healthy organs.
    This method is applied to multiple cancer treatment sites which emerge new challenge in the context of prediction, and data processing.

  • Felix Desrosiers

    Ph.D. candidate
    Faculté de médecine
    Université Laval

    Student
    Directeur.e(s) de recherche
    Vicky Drapeau
    Yves De Koninck
    Philippe Després
    Collaboration
    PULSAR
    Start date
    Title of the research project
    Design, operationalization and validation of a sustainable health evaluation model adapted to a digital platform
    Description

    The project focuses on the design, operationalization and validation of a sustainable health evaluation model.
    This model will be adapted to a digital platform and based on solid theoretical and conceptual foundations. Furthermore, it will gather valid indicators and will be supplied by data showing a global and ecosystem conception of health.
    Once operationalized, implemented and validated in a cohort study, this model will represent an innovative strategy for sustainable health through improved technologies and intervention methods.
     

    • Title of the research project
    Design, operationalization and validation of a sustainable health evaluation model adapted to a digital platform
    Description

    The project focuses on the design, operationalization and validation of a sustainable health evaluation model.
    This model will be adapted to a digital platform and based on solid theoretical and conceptual foundations. Furthermore, it will gather valid indicators and will be supplied by data showing a global and ecosystem conception of health.
    Once operationalized, implemented and validated in a cohort study, this model will represent an innovative strategy for sustainable health through improved technologies and intervention methods.

    Title of the research project
    Data pipelines in diagnostic radiology
    Description

    This project aims to create data pipelines in diagnostic radiology in order to supply analysis and visualization tools.

    The first pipeline is intended for data anonymization according to standard DICOM while the second one allows to supply Kibana (Elasticsearch) or Superset (Apache) platforms.

    The Airflow orchestrator (Apache) is used to automate the execution of pipelines which could eventually supply dynamic dashboards. 
     

  • Antoine Bouchard

    Undergraduate intern
    Faculté des sciences et de génie
    Université Laval

    Student
    Directeur.e(s) de recherche
    Philippe Després
    Start date
    Title of the research project
    Data pipelines in diagnostic radiology
    Description

    This project aims to create data pipelines in diagnostic radiology in order to supply analysis and visualization tools.

    The first pipeline is intended for data anonymization according to standard DICOM while the second one allows to supply Kibana (Elasticsearch) or Superset (Apache) platforms.

    The Airflow orchestrator (Apache) is used to automate the execution of pipelines which could eventually supply dynamic dashboards. 
     

    • Title of the research project
    The health data legal framework and associated medical liability mechanisms, within the artificial intelligence development framework : comparative European and North American prospects
    Description

    The research project is about the suitability of laws, legal principles and general framework surrounding health-related data, including those regulating the involved medical liability, in Canada and in the European Union. 

  • Maelenn Corfmat

    Ph.D. candidate
    Faculté de droit
    Université de Montréal

    Student
    Directeur.e(s) de recherche
    Catherine Régis
    Anne Debet
    Start date
    Title of the research project
    The health data legal framework and associated medical liability mechanisms, within the artificial intelligence development framework : comparative European and North American prospects
    Description

    The research project is about the suitability of laws, legal principles and general framework surrounding health-related data, including those regulating the involved medical liability, in Canada and in the European Union. 
    It aims to identify its weaknesses and aspires to provide regulatory solutions that are more appropriate to the realities of artificial intelligence. These solutions should better balance private and public, individual, social, commercial and health-related interests at stake. Also, this project considers a different view of the law and of our current legal systems with missing satisfactory answers.
     

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