Why Medicine Needs Deep Learning - Brendan Frey
Channel: bhadeshia123
Date: 16/04/2016

My research on deep inference and learning reaches back to the wake-sleep algorithm, published in 1995, and the paper that David MacKay and I wrote in 1996 showing that belief propagation in graphs with cycles can be used for accurate inference. Most of my time is now spent on genomic medicine. Deep learning will transform medicine, but not in the way that many advocates think. The amount of data times the mutation frequency divided by the biological complexity and the number of hidden variables is small, so downloading a hundred thousand genomes and training a neural network won't cut it. There is what I call a "genotype-phenotype gap" and the value of closing this gap exceeds Google's $200B ad market. I believe that the only way to bridge this gap is to build machine learning systems that properly incorporate biological knowledge. I'll describe this approach, which is being pursued by dozens of young investigators, has improved our ability to “read the genome”, and will, I believe, be an indispensable component in the future of medicine.

Part of a symposium to celebrate the work of Professor Sir David MacKay FRS. The symposium was held over the period 14-15 March 2016.

http://divf.eng.cam.ac.uk/djcms2016/