radiology-skills
A full-stack skill package for medical imaging research, covering the entire process from topic selection to grant application.
- Type
- Agent Skill
- Open source
- Yes
- GitHub Stars
- ★ 1.0k
- Source
- skill-github
- Repository
- github.com/huang-sir1/radiology-skills
Overview
radiology-skills is a comprehensive skill package for medical imaging research, developed by a team of first authors who have published original research in Radiology. This package aims to assist researchers in completing tasks such as identifying cutting-edge research topics, literature review, study design, annotation standards, statistical analysis, figure planning, mechanism exploration, multi-center validation, use of public databases, ethics and reproducibility, manuscript writing, pre-submission review, journal selection and submission, grant proposal writing, clinical translation, and revision responses. It is based on high-quality literature and summarizes publication patterns in medical imaging AI, radiomics, deep learning in imaging, imaging genomics, and clinical translation. The package provides 22 virtual specialty consultants, covering the complete research workflow from data feasibility assessment to grant proposal writing.
Capabilities
- ▪Frontier topic identification and innovation point mining
- ▪Study design and validation plan development
- ▪Literature search and dataset validation
- ▪Standard operating procedure design for lesion delineation
- ▪Data compliance and de-identification processing
- ▪Statistical analysis and figure planning
Use cases
Setup
npm install radiology-skills
This information was compiled by AI from public sources and may contain inaccuracies — please refer to the source.
FAQ
Who is this skill package suitable for?
Clinical research teams with medical imaging data but uncertain about research direction, as well as researchers aiming to publish in high-impact journals.
How do I call these skills?
Through API calls; refer to the example code in the documentation for details.
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