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/medical-imaging-review

Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests for

From plugin
auto-empirical-research-skills
3.3k200 skills146 agents
Install
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill medical-imaging-review --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/medical-imaging-review

Context preview

The summary Claude sees to decide when to auto-load this skill.

Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests for

SKILL.md

medical-imaging-review.SKILL.md
name: medical-imaging-review
description: >
  Write comprehensive literature reviews for medical imaging AI research.
  Use when writing survey papers, systematic reviews, or literature analyses
  on topics like segmentation, detection, classification in CT, MRI, X-ray,
  ultrasound, or pathology imaging. Triggers on requests for "review paper",
  "survey", "literature review", "综述", "systematic review", or mentions of
  writing academic reviews on deep learning for medical imaging.
metadata:
  author: user
  version: "2.0.0"
allowed-tools:
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - Bash
  - WebSearch
  - WebFetch
  - Task
  - mcp__arxiv-mcp-server__search_papers
  - mcp__arxiv-mcp-server__download_paper
  - mcp__arxiv-mcp-server__read_paper
  - mcp__pubmed-mcp-server__pubmed_search_articles
  - mcp__zotero__zotero_search_items
  - mcp__zotero__zotero_get_item_fulltext

<!-- ╔══════════════════════════════════════════════════════════════╗ ║ 本文件为开源 Skill 原始文档,收录仅供学习与研究参考 ║ ║ CoPaper.AI 收集整理 | https://copaper.ai ║ ╚══════════════════════════════════════════════════════════════╝

来源仓库: https://github.com/luwill/research-skills 项目名称: research-skills 开源协议: MIT License 收录日期: 2026-04-02

声明: 本文件版权归原作者所有。此处收录旨在为社会科学实证研究者 提供 AI Agent Skills 的集中参考。如有侵权,请联系删除。 -->

Medical Imaging AI Literature Review Skill

Write comprehensive literature reviews following a systematic 7-phase workflow.

Quick Start

1. **Initialize project** with three core files:

  • `CLAUDE.md` - Writing guidelines and terminology
  • `IMPLEMENTATION_PLAN.md` - Staged execution plan
  • `manuscript_draft.md` - Main manuscript

2. **Follow the 7-phase workflow** (see [references/WORKFLOW.md](references/WORKFLOW.md))

3. **Use domain-specific templates** (see [references/DOMAINS.md](references/DOMAINS.md))

---

Core Principles

Writing Style

  • **Hedging language**: "may", "suggests", "appears to", "has shown promising results"
  • **Avoid absolutes**: Never say "X is the best method"
  • **Citation support**: Every claim needs reference
  • **Limitations**: Each method section needs a Limitations paragraph

Required Elements

  • **Key Points box** (3-5 bullets) after title
  • **Comparison table** for each major section
  • **Performance metrics**: Dice (0.XXX), HD95 (X.XX mm)
  • **Figure placeholders** with detailed captions
  • **References**: 80-120 typical, organized by topic

Paragraph Structure

Topic sentence (main claim)
  → Supporting evidence (citations + data)
  → Analysis (critical evaluation)
  → Transition to next paragraph

---

Literature Sources

Use multi-source strategy for comprehensive coverage:

| Source | Best For | Tools | |--------|----------|-------| | ArXiv | Latest DL methods, preprints | `search_papers`, `read_paper` | | PubMed | Clinical validation, peer-reviewed | `pubmed_search_articles` | | Zotero | Existing library, organized refs | `zotero_search_items` |

For MCP configuration details, see [references/MCP_SETUP.md](references/MCP_SETUP.md).

---

Standard Review Structure

# [Title]: State of the Art and Future Directions

## Key Points
- [3-5 bullets summarizing main findings]

## Abstract

## 1. Introduction
### 1.1 Clinical Background
### 1.2 Technical Challenges
### 1.3 Scope and Contributions

## 2. Datasets and Evaluation Metrics
### 2.1 Public Datasets (Table 1)
### 2.2 Evaluation Metrics

## 3. Deep Learning Methods
### 3.1 [Category 1]
### 3.2 [Category 2]
(Table 2: Method Comparison)

## 4. Downstream Applications

## 5. Commercial Products & Clinical Translation (Table 3)

## 6. Discussion
### 6.1 Current Limitations
### 6.2 Future Directions

## 7. Conclusion

## References

---

Method Description Template

### 3.X [Method Category]

[1-2 paragraph introduction with motivation]

**[Method Name]:** [Author] et al. [ref] proposed [method], which [innovation]:
- [Key component 1]
- [Key component 2]
Achieves Dice of X.XX on [dataset].

**Limitations:** Despite advantages, [category] methods face:
(1) [limit 1]; (2) [limit 2].

---

Citation Patterns

# Data citation
"...achieved Dice of 0.89 [23]"

# Method citation
"Gu et al. [45] proposed..."

# Multi-citation
"Several studies demonstrated... [12, 15, 23]"

# Comparative
"While [12] focused on..., [15] addressed..."

---

Reference Files

| File | Purpose | |------|---------| | [references/WORKFLOW.md](references/WORKFLOW.md) | Detailed 7-phase workflow | | [references/TEMPLATES.md](references/TEMPLATES.md) | CLAUDE.md and IMPLEMENTATION_PLAN.md templates | | [references/DOMAINS.md](references/DOMAINS.md) | Domain-specific method categories | | [references/MCP_SETUP.md](references/MCP_SETUP.md) | MCP server configuration | | [references/QUALITY_CHECKLIST.md](references/QUALITY_CHECKLIST.md) | Pre-submission quality checklist |

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📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |

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