On 19 May 2021 and working with NHS England & NHS Improvement (NHSEI) and NHSX we launched the AnalystX machine learning challenge.
Creating a predictive model that will help the NHS recover from COVID-19 pandemic.
The challenge is open to all analysts across health and care, and the aim is to promote collaboration, improve data science skills and highlight the huge opportunities machine learning presents in improving patient outcomes during the next phase of the COVID-19 pandemic.
The challenge aims to encourage models that are explainable to the system. Challenge entries should be accompanied with evidence or reason(s) for all outputs and with explanations that are understandable to individual users.
The winning entry will be announced in October 2021 on the AnalystX machine learning workspace -please subscribe to the workspace to be alerted for more details
- Ming Tang – NHSE/I
- Ben Goldacre –The DataLab, Oxford University
- Sarah Culkin – NHSX
- Chris Mainey – NHSE/I
- Mark Frankish – SAS
- And our very own Bruno Petrungaro.
Full details about the challenge can be found on the dedicated Machine Learning space on Analyst X.
More information to follow…
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