Cloud computing guide for researchers – Text mining for healthcare research using Cortana Intelligence


The explosion in the quantity of medical literature over the last couple of decades is making it increasingly difficult to quickly develop robust guidance to bring research into real-world practice for patients and citizens around the world. Researchers at University College London and Cochrane are working together to apply AI and machine learning to analyze thousands of reports to automatically select ones to include in systematic reviews in the Cochrane Transform Project.

This new approach is successfully saving weeks of monotonous work, freeing up the expert health care reviewers to spend their time and energy on high-level analysis. Professor James Thomas is using Cortana Intelligence to quickly develop and deploy AI solutions in the cloud, building machine learning classifiers that can sift though thousands of research publications and automatically sort them. This is speeding up decision-making to make treatments available for 65 million citizens across the UK National Health Service, and all over the world.

The flexibility of the Microsoft Cloud means that the researchers can quickly create customized systems tailored for each clinical assessment group. This is then made usable by researchers worldwide through the EPPI-Reviewer cloud service, which is now running on Microsoft Azure.

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