Summary of Emory Knee Radiograph (mrkr) Dataset, by Brandon Price et al.
Emory Knee Radiograph (MRKR) Dataset
by Brandon Price, Jason Adleberg, Kaesha Thomas, Zach Zaiman, Aawez Mansuri, Beatrice Brown-Mulry, Chima Okecheukwu, Judy Gichoya, Hari Trivedi
First submitted to arxiv on: 30 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The Emory Knee Radiograph (MRKR) dataset is a large-scale collection of knee radiographs from 83,011 patients, with 40% being African American. The dataset includes imaging data in DICOM format along with detailed clinical information, such as patient-reported pain scores and diagnostic codes. This provides a valuable resource for researchers and clinicians to study osteoarthritis and related outcomes, particularly among minority populations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The Emory Knee Radiograph (MRKR) dataset is a big collection of knee X-ray images from 83,011 people. It’s special because 40% of those people are African American. The data includes information about the pictures, like what kind of picture it is and if there’s any hardware in the picture. This helps doctors and researchers learn more about osteoarthritis and how to help people with it. |
