PHM Standards in the Machine Learning Domain- Panel July 28 at the PHME20 Virtual Event

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jeff bird
Joined: 2009-05-29

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

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

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)

PHHE20- Intro Standards Panel v1.pdf878.58 KBJuly 26, 2020 - 6:01pm
understanding_artificial_intelligence_ethics_and_safety.pdf5.42 MBJuly 27, 2020 - 4:44am
mhra-ai-paper-ML Standard.pdf531.15 KBJuly 27, 2020 - 4:44am
overview of AI Standarization 2019.pdf1.14 MBJuly 27, 2020 - 4:45am

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