Prevalence of machine manufacture models in the MIMIC-CXR database
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Description
Prerequisites
- [X ] Put an X between the brackets on this line if you have done all of the following:
- Checked the online documentation: https://mimic.mit.edu/
- Checked that your issue isn't already addressed: https://github.com/MIT-LCP/mimic-code/issues?utf8=%E2%9C%93&q=
Description
Machine Manufacturers have an established effect on deep neural network performance - https://pubs.rsna.org/doi/full/10.1148/ryai.220165
Although it is understood that X-Ray machine manufacturer information cannot be released at a DICOM-level, it would be useful if summary table could be provided for the MIMIC-CXR dataset, outlying the overall machine manufacturers used and the proportion of images acquired by each machine. This would aid greatly in discussing model generalisabilities when using the MIMIC-CXR dataset.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the MIMIC-CXR documentation and the linked paper on machine-manufacturer effects, then determine what manufacturer metadata is available without exposing DICOM-level information. Done means providing a summary table of the manufacturers represented in MIMIC-CXR and the proportion of images acquired by each.
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Assessment
- Domain
- databases
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100