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Researchers and Industry benefit from the first AI in health and care, study group workshop.

20 June 2019

Medical instruments, tweezers,. scalpel, scissors and dip bag with a medical chart.

This 3-day study group which was held in the School of Mathematics, brought together researchers who worked on tackling healthcare challenges from industry.  The event was jointly organised by Innovate UK and the Data Innovation Research Institute (DIRI), and chaired locally by Paul Harper (MATHS and DIRI) and Steven Schockaert (Computer Science) along with Matt Butchers, Knowledge Transfer Manager of Industrial Mathematics at Innovate UK/KTN.

During the first morning, three companies Knee Tracker, isardSAT and Oxford Brain Diagnostics, outlined their challenges and provided data. Researchers then selected which problem to work on over the proceeding 2.5 days, with final group presentations made on the closing afternoon. The problems focused on:

  • Machine Learning for Improved Osteoarthritis Prediction (Knee Tracker)
  • AI and Earth Observations for the Prediction of Malaria Outbreak Risk (isardSAT)
  • Better Bias-field Correction in MRI Through Machine Learning (Oxford Brain Diagnostics)

Clement Twumas (first year PhD student of Prof Owen Jones) joined the Knee Tracker group together with Andrey Pepelyshev, Yoyo Zhou (MEDIC), Prof. Irena Spasic (COMSC and DIRI) and Shameem Sampath (Knee Surgeon). Below is a link to the presentation which has been simplified such that both modelling and non-modelling specialists as well as non-technical experts can easily understand the application of Machine learning or Artificial Intelligence approaches to uncover hidden findings for any given data.

https://drive.google.com/file/d/1dB1NWrw9d2mUhlFO-2kUVCdfpIi3FgtD/view?ts=5ce94852

Participants had a very enjoyable and productive 3 days, with a great deal of satisfaction being able to work on important medical problems and ultimately to help the companies with some insights using data science and modelling methods. We look forward to running a similar event in 2020.

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