openmedical/registry
← registry

summarize-radiology-findings

imported

software/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.

summarize-radiology-findings project image
GitHub preview card for yuhaozhang/summarize-radiology-findings. Served by its origin, not stored here, and not covered by this registry’s licence.
record
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
built by · 1

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.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • biomedicusnatural-language-processing · nlp

    BioMedICUS: A biomedical and clinical NLP engine.

  • harmonynatural-language-processing · nlp

    The Harmony Python library: a research tool for psychologists to harmonise data and questionnaire items. Open source.

  • medpromptjssummarization

    MedpromptJS: Base classes for easy GenAI app development and reference implementation of LLM-in-the-Loop CQL on unstructured data.

  • aditmedicine · radiology

    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.

  • RadGraph-ITnlp · radiology

    Italian NLP package for extracting clinical entities and relations from free-text radiology reports.

  • clinical_trial_risknatural-language-processing · nlp

    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

sources
  1. api.github.com/repos/yuhaozhang/summarize-radiology-findings
    retrieved 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 →

machine-readable

/v1/entries/26.json→ .entries["summarize-radiology-findings"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.