Summary of Chexpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats, by Pierre Chambon et al.
CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats
by Pierre Chambon, Jean-Benoit Delbrouck, Thomas Sounack, Shih-Cheng Huang, Zhihong Chen, Maya Varma, Steven QH Truong, Chu The Chuong, Curtis P. Langlotz
First submitted to arxiv on: 29 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents CheXpert Plus, a publicly available dataset for radiology, which aims to enhance the performance and fairness of AI models in this field. The dataset consists of 36 million text tokens, including impression tokens, anonymized patient health information (PHI), and paired with high-quality images. This dataset is unique as it allows for cross-institution training at scale, enabling more accurate AI-assisted diagnoses. With over 13 million impression tokens and nearly 1 million PHI spans anonymized, CheXpert Plus represents the largest text de-identification effort in radiology. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary CheXpert Plus is a big deal! It’s like a super-sized version of an old dataset called CheXpert that was released five years ago. Now, people can use this new data to make even better AI models that help doctors with medical imaging and diagnosis. The dataset has millions of words and images from hospitals all around the world. It’s special because it helps keep patient information private while still allowing researchers to train their AI models. This means that AI-assisted diagnoses will get even more accurate, which can improve medical care for patients. |
