Welcome Deep Learners!

This document provides all the information you need to participate in the RSNA AI Deep Learning Lab. This set of classes provides a hands-on opportunity to engage with deep learning tools, write basic algorithms, learn how to organize data to implement deep learning and improve your understanding of AI technology.

The classes will be held in the RSNA AI Deep Learning Lab classroom, which is located in the Lakeside Learning Center, Level 3. Here's the schedule of classes. CME credit is available for each session.

All lessons are designed to run in Google Colab, which is a free web-based version of Jupyter hosted by Google. You will need a Google account (eg, gmail) to use Colab. If you don't already have a Google account, please create one in advance at the account sign-up page. You can delete the account when you complete the lessons if you wish.

We recommend that you use a computer with a recent vintage processor running the Chrome browser.

Lesson : Pneumonia Detection Model Building (Beginner friendly)

Lesson : MedNIST Exam Classification with MONAI (Beginner friendly)

Lesson : DICOM Data Wrangling with Python (Beginner friendly)

Lesson : CT Body Part Classification (Beginner friendly): Notebook #1, Notebook #2

Lesson : YOLO: Bounding Box Segmentation & Classification: Practice Notebook, Complete Notebook

Lesson : Integrating Genomic and Imaging Data with TCGA-GBM

Lesson : Generative Adversarial Networks

Lesson : Object Detection & Segmentation (Beginner friendly)

Lesson : Working with Public Datasets: TCIA & IDC (Beginner friendly)

Lesson : NLP: Text Classification with RNNs & Transformers: Notebook #1, Notebook #2

Lesson : Multimodal Fusion for Pulmonary Embolism Detection Using CTs and Patient EMR

Lesson : Data Processing & Curation for Deep Learning (Beginner friendly)

Lesson : Basics of NLP in Radiology (Beginner friendly)