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RSNA AI Deep Learning Lab 2023

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

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.

Class Schedule

Date / Time Session Folder Notebooks
Sunday, 26 Nov 2023
Sun 10:00-11:00am Basics of NLP in Radiology (Beginner friendly) Notebook
Sun 11:00am-12:30pm CT Body Part Classification (Beginner friendly) Train notebook, Inference notebook
Sun 2:30-3:30pm Data Processing & Curation for Deep Learning (Beginner friendly) Notebook
Monday, 27 Nov 2023
Mon 9:00-10:00am DICOM Data Wrangling with Python (Beginner friendly) Notebook
Mon 10:30-11:30am NCI Imaging Data Commons: Curated data and Reproducible AI workflows (Beginner friendly) Notebook
Mon 12:00-1:00pm ChatCTP: DICOM De-Identification Using ChatGPT (Beginner friendly) Notebook
Mon 1:30-2:30pm NLP: Text Classification with Transformers (Beginner friendly) See README for pre-course prep, Report Classification, Chat with ACR Contrast Manual
Mon 3:00-4:00pm Accessing freely available public datasets from The Cancer Imaging Archive (TCIA) (Beginner friendly) Notebook
Tuesday, 28 Nov 2023
Tues 9:00-10:00am Zero-code Implementation of Federated Learning for Radiology (Beginner friendly) TBD
Tues 10:30-11:30am MIDRC: Building & Using AI-Ready Datasets from a Massive Open Data Commons (Beginner friendly) See README in session folder
Tues 12:00-1:00pm MedNIST Exam Classification with MONAI (Beginner friendly) TBD
Tues 1:30-2:30pm Evaluating Fairness of AI Models in Radiology TBD
Tues 3:00-4:00 pm Best Practices for Model Training: Architectures, Hyperparameters & Optimization TBD
Wednesday, 29 Nov 2023
Wed 10:00-11:00 am Object Detection in Medical Imaging Notebook
Wed 11:30am-12:30pm Medical Image Generation Notebook
Wed 1:00-2:00pm Accelerate your AI-based medical imaging research with MONAI Core on SageMaker See README in session folder
Wed 2:30-3:30pm Developing & Implementing a 3D Segmentation Model: From DICOM to Deployment Notebooks in session folder: see README
Thursday, 30 Nov 2023
Thurs 9:00-10:00am DICOM In, DICOM Out for Segmentation Notebook
Thurs 10:30-11:30 am Deploy Your Own Model in HuggingFace TBD

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