Case Study: TensorFlow in Medicine - Retinal Imaging (TensorFlow Dev Summit 2017)

Опубликовано 16 февраля 2017, 2:37

Explore this illuminating ML medical case study where Lily Peng dives into the realm of diabetic retinopathy, the fastest growing cause of blindness linked to diabetes. Witness how the power of machine learning was trained to meticulously analyze retinal fundus images for precise diagnosis. Lily Peng guides you through the pivotal project phases, from acquiring a dataset, training a deep network, and evaluating the results.Embark on this journey to uncover the seamless fusion of ML and medicine, unraveling new possibilities in the realm of healthcare.

Chapters:
0:00 - Introduction
3:42 - Training a model
5:15 - Demo
5:59 - Development and Validation of Deep Learning Algorithm for Detection of diabetic Retinopathy in Retinal Fundus Photographs
7:16 - Why we used TensorFlow
9:52 - Session wrap up

Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to the Google Developers channel at goo.gl/mQyv5L

#ML #medicialtechnology

event: TensorFlow Dev Summit 2017; re_ty: Publish;