What if we can detect anomalies of the colon at an early stage to prevent colon cancer? We are now in a technology era that it’s capable of doing impressive things that we didn’t imagine before. The use of artificial intelligence can detect more abnormalities than a conventional exam. Physicians should take advantage of this.
According to The American Cancer Society, in the United States, colorectal cancer is the third leading cause of cancer-related deaths in men and in women, and the second most common cause of cancer deaths. It’s expected to cause about 51,020 deaths during 2019.
AI & Creativity: Deep Dream comes true - Data Driven Investor
Artificial Intelligence always fascinated me. Not only as a useful set of tools, continuously evolving, but also as an…www.datadriveninvestor.com
Inspired by the #AISTARTUPCHALLENGE created by Siraj Raval, I decided to join the challenge! You can check it out at his Instagram account (Siraj Raval). The dynamic is to create an app that uses AI to solve a problem, get 3 paying customers for your app and submit it to win different prizes.
I will start with this healthcare project that classifies 8 different tissues in histological images of human colorectal cancer.
Colorectal Histology MNIST
Let’s get to know more about the dataset I will be using. I got this dataset at Kaggle and it contains a collection of textures in histological images of human colorectal cancer. It has about 5,000 histological RGB samples of 150X150 px, divided into eight tissue categories (specified by the folder name):
My goal is to identify each category. You can also create a model that classifies between Normal and Benign, but in this case, let’s identify all the different anomalies.