Machine learning for patient stratification from genomic data
As the cost and throughput of genomic technologies reach a point where DNA sequencing is close to becoming a routine exam at the clinics, there is a lot of hope that treatments of diseases like cancer can dramatically improve by a digital revolution in medicine, where smart algorithms analyze « big medical data » to help doctors take the best decisions for each patient. The application of machine learning-based techniques to genomic data raises however numerous computational and mathematical challenges that I will illustrate on a few examples of cancer patient stratification from gene expression or somatic mutation profiles.
Date:
27 January 2017, 15:30 (Friday, 2nd week, Hilary 2017)
Venue:
24-29 St Giles', 24-29 St Giles' OX1 3LB
Venue Details:
Large Lecture Theatre, Department of Statistics
Speaker:
Professor Jean-Philippe Vert (Mines ParisTech)
Organising department:
Department of Statistics
Organiser:
Professor Arnaud Doucet (University of Oxford)
Organiser contact email address:
events@stats.ox.ac.uk
Part of:
Distinguished Speaker Seminar
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Beverley Lane
