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Finding biomarkers to make personalized medicine more precise

Omics researchers are often faced with such large amounts of data that they are not able to analyze it quickly or pick out patterns hidden in the data. At the University of Alberta, a strong collaboration between cross disciplinary research teams has been able to bring machine learning and and artificial intelligence to bear on the problem and have produced some excellent results. One of those closely involved in harmonizing the next steps in precision medicine with the next steps in machine learning and artificial intelligence, is David Wishart.
He is Director of The Metabolomics Innovation Centre at the University of Alberta which receives support from Genome Alberta.
One of the advantages of machine learning is being able to find things you were not really looking for. In this conversation with freelance broadcaster Don Hill, Dr. Wishart talks about a surprise discovery that offered some insight into stillbirths, and about the advances that are being made as we become better able to analyze data.

Finding biomarkers to make personalized medicine more precise

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