In the last decades, the term “Big data” has been used to describe the rapid increase in volume, variety and velocity of information available in the vast majority of the aspects of our lives and -of course - in healthcare and biomedicine. Different methods for improving data collection, storage, cleaning, processing and interpretation continue to be developed and represent the key stones for the “use” of the big data knowledge. Data mining is the process of evaluating existing data sets to extract new insights from them. These methods belong to machine learning (ML), statistics and database systems areas. The course will: present a set of ML techniques that can be applied to the data set to analyse the existing informations give an overview on the applications of data mining in healthcare and biomedicine of the 3rd millennium address the issue of ethical and legal aspects of data mining

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The Course is divided in lessons: (14 hours) and lab work (6 hours) 1) Introduction 2) Dataset construction: Data Storage, data Cleaning, Missing data 3) Methods: Clustering and Associative rules 4) Applications in healthcare and biomedicine 5) Ethical aspects of data mining in healthcare 6) Legal aspects of data mining in healthcare During lab lessons students will apply data mining techniques to real life data.

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Presentazione orale

P.D.2-2 - Marzo