Explorations of Deep Learning in Medicine Means Hope to Billions
This is super exciting: deep learning could bring medical care at scale to billions of people in emerging markets. Jeremy Howard, the former president of Kaggle, and a former distinguished scientist at Stanford, is working on a cutting edge technology with a very important purpose: push the limits of deep learning machine intelligence techniques to deliver medical diagnosis to billions of people who don’t have adequate access to medical services.
According to the World Economic Forum’s 2014 report on health systems in emerging economies, it will take 300 years for Nigeria and similar emerging economies to train enough doctors for delivering necessary medical services for all of its population. Howard is aiming to use deep learning to bring some of those services to the ones who need it the most.
The idea is to use deep learning on PACs in hospitals to develop features and train models. PACS (Picture Archiving and Communication Systems) is a healthcare technology for storage and management of medical images such as MRIs, CT scans, x-rays, etc. Howard already has demos where his deep learning models can accurately identify hard-to-detect fractures.
Howard started Enlitic in August 2014 and only after a year, his company raised another round of investments totaling 10M. But what is more important than that is that his technology will now be field tested at 80 some medical centers, giving them access to PACs.
Wikipedia describes Howard as a wunderkind. I’m deeply impressed by how he is applying his talent to change the world in such a positive manner. Big kudos to Howard and his team!
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