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    jeff bird
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    Standards affect 80% of the world’s business: knowledge and synergies are captured across domains. In condition monitoring and diagnostics, standards are available for machine learning (ML) like ISO 13379-2:2015. Such general procedures to develop and implement such data driven approaches are supplemented by more generic data mining studies. These look at standards for the tasks to be performed, those for supporting technology and also process standards for conducting a Machine Learning project.

    Complimentary registration at phmeurope.org


    Standards affect 80% of the world’s business: knowledge and synergies are captured across domains. In condition monitoring and diagnostics, standards are available for machine learning (ML) like ISO 13379-2:2015. Such general procedures to develop and implement such data driven approaches are supplemented by more generic data mining studies. These look at standards for the tasks to be performed, those for supporting technology and also process standards for conducting a Machine Learning project.

    Complimentary registration at phmeurope.org

    This panel will start with 5-10 minute highlights from the panelists on their experiences and challenges in this domain. Much of the time will be available for a virtual discussion with the audience of some of the following questions:

    1. Have standards or compiled bodies of knowledge helped machine learning innovations and applications? What is missing?
    2. Can standards help in ML tasks, supporting technology and project processes?
    3. Are a formal taxonomy, definitions of inputs, outputs, and validation procedures needed?
    4. How can hybrid (ML with physics) approaches be facilitated to exploit all of our knowledge of a system?
    Plus provocative questions from the panel!
    AND a general discussion via Google Meet chat questions t0o the panel
    See an outline in the attached presentation
    Here also are some great reference documents from Yvonne at the health care AI interface

    Panelists:
    Daniel Gagar (Siemens)
    Danilo Giordano (Politecnico di Torino)
    Steve King – Invited (Cranfield University)
    Dr Huiqi (Yvonne) Lu and Dr Samaneh Kouchaki (The Institute of Biomedical Engineering – Oxford University)

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