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- Enable new and inexperienced users to gain the skills required for the data management, analysis, and visualization tasks that they seek using the R language.
- Facilitate the sharing of approaches, programming techniques, and code among current users.
- Involvement with the growing global community of epidemiologists and developers using R to advance the science of disease surveillance.
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- R Application for Biosurveillance Google Group
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Building meaningful machine learning models for disease prediction
Shirin Glander: I’m a bioinformatician at the University Hospital of Münster in Germany, where I’m responsible for bioinformatics analyses of Next Generation Sequencing data. I’ve earned my PhD from the University of Münster and my overarching interest has always been evolutionary biology and genetics of diseases. Now, I am mainly working on questions relating to immunology – specifically inflammation, immune tolerance and auto-inflammatory diseases. I’m a big fan of R and I write a blog where I explore techniques for analyzing different data sets and I teach ballroom and Latin dance courses in my spare time.
Dr. Shirin Glander will go over her work on building machine-learning models to predict the course of different diseases. She will go over building a model, evaluating its performance, and answering or addressing different disease related questions using machine learning. Her talk will cover the theory of machine learning as it is applied using R.