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Data quality supporting AI in Life Sciences webinar 10 dec 2018


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Data Quality is at the heart of AI/ML and is one of the key challenges we face in Life Sciences to make AI a success.

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Data quality supporting AI in Life Sciences webinar 10 dec 2018

  1. 1. 30 November, 2018 Data Quality in Machine Learning & Artificial Intelligence Pistoia Alliance Centre of Excellence for AI in Life Sciences & Health Moderator: Vladimir Makarov 10 December 2018
  2. 2. This webinar is being recorded
  3. 3. ©PistoiaAlliance 330 November, 2018 Questions Welcome
  4. 4. ©PistoiaAlliance Data Quality in Machine Learning and Artificial Intelligence 430 November, 2018 • Introductions and overviews – Pistoia Alliance Centre of Excellence for AI in Life Sciences and Health – Our panelists today • Panel Discussion • Wrap-up and next meetings – London AI Workshop 12 March 2019
  5. 5. ©PistoiaAlliance • • • • • • • •
  6. 6. ©PistoiaAlliance • • • • • • •
  7. 7. E.
  8. 8. ©PistoiaAlliance Introduction to Today’s Speakers Terry Stouch, Science for Solutions Jamie Powers, Cambridge Semantics Isabella Feierberg, Astra Zeneca Jabe Wilson, Elsevier Sirarat Sarntivijai, ELIXIR
  9. 9. ©PistoiaAlliance • Define “data quality” - FAIR? Open? Shareable? What are metrics for FAIR-ness of data? How accurate are metadata? – How to measure data quality? – Would a standard set of data quality dimensions (e.g. Completeness, Accuracy, Consistency, Validity, Uniqueness, Timeliness) benefit the lifesciences industry? • Discuss metadata standards, as-is and to-be • How high level of quality is needed at specific points of research work cycle? – Various models in AI are more or less sensitive to outliers, missing values, etc
  10. 10. ©PistoiaAlliance Additional Questions Sent In Earlier 12 • How to use AI to measure or improve the quality of data? • What are the top application areas of AI in life science where improving data quality would help? • Rather than improving data quality, what about focusing AI efforts on data that is known to be of high quality? ... where would this direct us? • What are some real examples of how someone improved the quality of data for AI which lead to important results? • Does the industry and regulator focus on Data Integrity and ALCOA+, which is focused on primary use of data, hinder or support data quality initiatives?
  11. 11. AI/ML London Workshop 12 March 2019 Registrations are now open for the London workshop, with speakers from Pharma, Biotech and Research Organisations - more details
  12. 12. Upcoming Pistoia Alliance Webinar Knowledge Graphs for Pharma: A perspective from the PhUSE Project 'Clinical Trials Data as RDF' Date/Time: January 24th, 2019 11am ET/4pmGMT/5pm CET Speaker: Tim Williams (UCB and PhUSE)
  13. 13. @pistoiaalliance www.pistoiaalliance.or g Thank You