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American College of Radiology's "Define-AI" Use Case Directory

The ACR Data Science Institute's Define-AI Use Case Directory was created to empower AI developers to produce algorithms that are clinically relevant, ethical, and effective. Each use case provides narrative descriptions and flow charts which specify the health care goal of the algorithm, the required clinical input, how it should integrate into the clinical workflow and how it will interface with users and tools.  Publicly available datasets which could potentially be used to tackle these use cases are listed at the bottom of each Use Case page, many of which include TCIA datasets.  Visit https://www.acrdsi.org/DSI-Services/Define-AI to learn more.

Third party tips and tutorials for applying deep learning to medical imaging data

1. RSNA Deep Learning Lab courses
   1. https://github.com/RSNA/AI-Deep-Learning-Lab-2023
   2. https://github.com/RSNA/AI-Deep-Learning-Lab-2022
   3. https://github.com/RSNA/AI-Deep-Learning-Lab-2021
   4. https://github.com/RSNA/AI-Deep-Learning-Lab (2019)
2. https://mayo-radiology-informatics-lab.github.io/MIDeL/index.html - MIDeL is a website to help healthcare professionals and medical imaging scientists learn to apply deep learning methods to medical images. It consists of a comprehensive text (think of an electronic textbook) combined with actual code examples to help you learn about Deep Learning.
3. https://github.com/RSNA/MagiciansCorner - Notebooks, datasets, other content for the Radiology:AI series known as Magicians Corner by Brad Erickson
4. http://modelhub.ai/ - a repository of self-contained deep learning models pretrained for a wide variety of applications which includes many models trained with TCIA datasets along with example notebooks
5. https://www.youtube.com/watch?v=-XUKq3B4sdw - how a radiologist interprets lung CTs
6. https://www.kaggle.com/gzuidhof/full-preprocessing-tutorial - how to pre-process images for deep learning
7. https://theaisummer.com/medical-image-coordinates/ - DICOM deep learning for medical imaging novices
8. https://developer.nvidia.com/clara-medical-imaging - NVIDIA package for simplifying deep learning tasks in medical imaging
9. https://forums.fast.ai/t/fastai-v2-has-a-medical-imaging-submodule/56117 - FastAI package for simplifying deep learning in medical imaging
10. "TCIA as a Centralized Data Resource for Development of AI" from RSNA 2019
11. https://www.kaggle.com/marcovasquez/basic-eda-data-visualization - RSNA intracranial hemorrhaging guide