Full session (30 minutes)
deep learning
Data Science

As data scientists in healthcare, we wanted to enhance our experience in Deep Learning. Fortunately, the "Machine & Deep learning Israel" community managers decided to frontal teach, for the second time, the Stanford University course: "Convolutional Neural Networks for Visual Recognition". We decided to jump at the opportunity.

In this lecture we will present our course final project, answering the following question: "Does Transfer Learning using a network trained to classify age and gender improves the detection of medical findings in chest X-ray images?".

This project is a collaboration with Zebra Medical Vision and is supervised by Ayelet Akselrod-Ballin, Eyal Toledano and Eli Goz. Extra credit to Amir Bar. Our classmates in the project are Netta Shemesh and Gil Baron

Dana Averbuch

Mila Orlovsky