Breast cancer classification in digital pathology using Python and Deep Learning

Breast cancer classification in digital pathology using Python and Deep Learning

Breast cancer is one of the leading cancer-related death causes worldwide, specially for women. In this talk, we will talk about how Deep Learning & Python could help pathologists to classify breast cancer microscopic images. The speaker will share his approach that won the “ICIAR 2018 Grand Challenge on Breast Cancer Histology images”, which was implemented in Python.

Refer to the papers for more details:

Buzzwords: Deep Learning, Digital Pathology, Breast Cancer, Whole-Slide Images, AI
Level: Advanced: Target audiences with advanced experience in python programming
Requirements to Audiences: Nil
Language: English

Speaker: Scotty Kwok (Hong Kong)

Speaker Bio: Scotty have been working in IT for 17+ years and is a seasoned developer in Java and Python. He is experienced in using various AI/Deep Learning frameworks (e.g. Keras, PyTorch, etc.) and neural networks (e.g. VGG, Inception, Resnet, etc). Scotty has a passion in solving medical problems and recently he won a global grand challenge in Breast Cancer image classification by using deep learning. Currently, he is on a journey to run a mixed- reality startup, SEBit, with his 3 other partners.

GitHub: https://github.com/scottykwok
LinkedIn: https://www.linkedin.com/in/scottykwok/
Twitter: https://twitter.com/scottykwok
Website/Blog: http://sebit.world