Nophar Geifman

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In this session we will cover the basics and key concepts of machine learning, what it is and how it can be applied. The emphasis will be on demonstrating, through real-world examples of application, how machine learning can benefit biomedical research, healthcare and precision medicine.

Nophar is a lecturer in Biomedical Data Analysis and Modelling at the Centre for Health Informatics at the University of Manchester. She holds a PhD in Biomedical Informatics and has completed her postdoctoral training with Prof. Atul J. Butte at Stanford University and the Institute for Computational Health Sciences at UCSF. Her interests lie in the fields of knowledge and data mining, endotype discovery, patient stratification and precision medicine, integration and meta-analyses of health-related big-data; and in improving the sharing and utility of these data. Her research focuses on the development and application of informatics techniques for analysis and discovery in various areas of medicine – particularly where conventional research methods have over-simplified the natural complexity of disease and care.

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