菜单
Access and apply professional radiology society guidelines. Use when user mentions "ACR criteria", "appropriateness rating", "guideline for", "society recommendation", "BI-RADS update", "dose reference levels", or "protocol guidelines".
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/aizech/clinical-skills --skill guideline-integration命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | guideline-integration |
| description | Access and apply professional radiology society guidelines. Use when user mentions "ACR criteria", "appropriateness rating", "guideline for", "society recommendation", "BI-RADS update", "dose reference levels", or "protocol guidelines". |
guideline_type (required): Type of guideline needed
appropriateness - ACR Appropriateness Criteriareporting - Structured reporting standards (BI-RADS, LI-RADS)dose - Radiation dose guidelinesprotocol - Imaging protocol recommendationsscreening - Screening eligibility guidelinesclinical_scenario (required): Brief description of clinical questionmodality (optional): Specific imaging modalityage_group (optional): Adult, pediatric, geriatric| Rating | Meaning |
|---|---|
| Usually Appropriate | 7-9 |
| May Be Appropriate | 4-6 |
| Usually Not Appropriate | 1-3 |
Returns structured JSON with:
guideline_type: appropriateness
clinical_scenario: acute flank pain suspected kidney stone
modality: CT
guideline_type: reporting
clinical_scenario: liver imaging surveillance
Links to:
Integrate AI detection into PACS workflow. Also use when setting up, configuring, or optimizing AI detection systems for medical imaging. Also covers Aidoc, Nvidia Clara, Zebra Medical, MaxQ AI, and Qure AI integration.
QA AI outputs, detect false positives/negatives, and validate AI results. Also use when evaluating AI system performance, reviewing AI-assisted findings, or conducting quality assurance on AI detection and reporting tools.
Guidance for AI-assisted structured reporting tools. Also use when the user mentions AI reporting, automated templating, speech-to-report, or wants to configure or optimize AI-assisted radiology reporting systems (RadAI, Abba, DeepRad).