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130 Exploring Genomic Innovation and Machine Learning in Public Health
Manage episode 446790586 series 3381906
Indhold leveret af Micro Binfie Podcast and Microbial Bioinformatics. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Micro Binfie Podcast and Microbial Bioinformatics eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
In this episode of the Micro binfie Podcast, host Andrew Page sits down with Tim Dallman at the 10th Bioinformatics Hackathon in Bethesda, Maryland. Tim shares insights from his work at Utrecht University in the Netherlands, where he focuses on genomic surveillance and machine learning models to predict disease risk and severity. They discuss the challenges of integrating genomic variation into predictive models, the importance of high-quality metadata, and the complexities of working with pathogens like Shiga toxin-producing E. coli. Tim also talks about his role at the WHO Pandemic and Epidemic Intelligence Hub and how global collaboration can drive innovation in public health genomics. Tune in to hear about cutting-edge research, the importance of interdisciplinary teamwork, and how genomic data can be harnessed for future pandemic preparedness.
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