Date

Mar 13, 2018 and Mar 14, 2018 

AI Workshop 13 March 

Material for the event is here

Thanks to all for coming to the workshop

Thanks to Mark Roberts for a great talk on an Intro to machine Learning and Artificial Intelligence 

Key output plus the conversations of the conference is the Centre of Excellence

• The workshop audience felt there was a strong demand for Best practices sharing

  • Avoiding bad practice

  • Promoting good practice

  • What does good quality look like?

  • Reproducibility of AI

  • What does a mature AI capability?

• Data challenges remain significant in creating quality datasets

• Key Data use cases & principles were described:

  • Access to all data - complex and correct'

  • Tidy and tabular

  • Quality definition

  • Avoid incompatible joining of data

  • Incentives for data creators

• Skills and the race of key talent remains, much recruitment underway across the sector

• Beyond the existing data areas of interest, new ones introduced:

  • ADHD and Neuroscience

  • Rare Disease

  • Translational models

  • Wearables

Conference Breakout Material and Discussions

Material for the event is here

Outcomes

Questions posed to the groups in the breakout session:

• Thinking about Large and disparate data sets, and manually intensive data exploration?

  • What manually intensive and data intensive tasks do you currently carry out?

  • Where do you see the value of AI in the next period?

Key themes that we prioriised

• Equivalence of terms, data standards and enrichment

• Instrument data, Feature extraction

• Chem informatics, Molecular property prediction

• Distributed data environment - protecting and preserving privacy

• NLP

• Clinical trials

Open

Next Steps

These ideas and examples from the workshop will be used to guide potential projects and data improvement activities

We will also cover them in the Centre of Excellence webinars, so if you want to express the current challenge in these areas get in touch