summarize-radiology-findings
importedsoftware/summarize-radiology-findings
Code and pretrained model for paper "Learning to Summarize Radiology Findings"
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- Apache-2.0(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Documentation
- unknown
- Tags
- medical-informatics · medical-natural-language-processing · medicine · natural-language-processing · nlp · radiology · summarization
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
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ADIT (Automated DICOM Transfer) is a swiss army knife to exchange DICOM data between various systems by using a convenient web frontend and DICOMweb compatible API client.
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Italian NLP package for extracting clinical entities and relations from free-text radiology reports.
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Clinical Trial Risk Tool for analysing clinical trial protocols using natural language processing and assessing the risk of ending uninformatively, developed by Fast Data Science
- api.github.com/repos/yuhaozhang/summarize-radiology-findingsretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2019-02-26, 85 stars, license reported as NOASSERTION. Category and schematic were assigned by keyword heuristics and are unreviewed. GitHub reported NOASSERTION; the licence was read from the LICENSE file as Apache-2.0, because GitHub's detector does not recognise open hardware licences.
Not yet verified by a human. Correct this record →
/v1/entries/26.json→ .entries["summarize-radiology-findings"]
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