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AI-Deep-Learning-Lab-2024

Data, notebooks, and articles associated with the RSNA AI Deep Learning Lab at RSNA 2024

Intro

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.

Requirements

Most 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. It is even better if you have administrator privileges on the computer with which you will be participating.

Class Schedule

Date / Time Session Folder Notebooks
Sunday, 1 Dec 2024
Sun 12:00-1:00pm DIY Deep Learning: Programming Setup for Beginners (Beginner friendly) Notebook
Monday, 2 Dec 2024
Mon 9:00-10:00am Basics of NLP in Radiology (Beginner friendly) Notebook
Mon 11:00am-12:00pm MIDRC - Cohort Building, Downloading, and Using Data for DL (Beginner friendly) Notebook
Mon 1:00-2:00pm Data Extraction from Radiology Reports with LLMs (Beginner friendly) Notebook
Mon 3:00-4:00pm NCI Imaging Data Commons: Curated data and Reproducible AI workflows (Beginner friendly) Notebook
Tuesday, 3 Dec 2024
Tues 9:00-10:00am Accessing freely available public datasets from The Cancer Imaging Archive (TCIA) (Beginner friendly) Notebook
Tues 11:00am-12:00pm ChatGPT: DICOM de-identification using ChatGPT (Beginner friendly) Notebook
Tues 1:00-2:00pm MIDRC: Contributing data - diversity, annotations, and harmonization (Beginner friendly) See session folder for links to session materials
Tues 3:00-4:00pm Deploy Your Own Model in Huggingface Notebook
Wednesday, 4 Dec 2024
Wed 9:00-10:00am Building a Simple Chest X-Ray Classification Model with TensorFlow (Beginner friendly) Notebook
Wed 11:00am-12:00pm Developing and Implementing a 3D segmentation model: from DICOM to deployment Notebook
Wed 1:00-2:00pm Quantifying Uncertainty in Deep Learning Notebook
Wed 3:00-4:00pm Best Practices for Model Training: Architectures, Hyperparameters & Optimization Notebook

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Data, notebooks, and articles associated with the RSNA AI Deep Learning Lab at RSNA 2024

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