medical-imaging-review

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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

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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

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

1. 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 |