medical-imaging-review

name: medical-imaging-reviewdescription: >  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

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)

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

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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

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Literature Sources

Use multi-source strategy for comprehensive coverage:

For MCP configuration details, see references/MCP_SETUP.md.

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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

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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].

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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..."

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Reference Files