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Medical Imaging Review 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 "review paper", "survey", "literature review", "综述", "systematic review", or mentions of writing academic reviews on deep learning for medic

$npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill medical-imaging-review
View this skill on GitHubbrycewang-stanford/Auto-Empirical-Research-Skills/skills/02-luwill-research-skills/medical-imaging-review/SKILL.md
Pack stars
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Pack installs
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Alyn Score
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Updated
35 h ago
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Install Medical Imaging Review

Pick your agent. Every command is ready to paste.

$npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill medical-imaging-review

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads medical-imaging-review when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the medical-imaging-review skill”. In Codex, type $medical-imaging-review.

The skill itself

SKILL.md

FolderGitHub

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)


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.


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 Detailed 7-phase workflow
references/TEMPLATES.md CLAUDE.md and IMPLEMENTATION_PLAN.md templates
references/DOMAINS.md Domain-specific method categories
references/MCP_SETUP.md MCP server configuration
references/QUALITY_CHECKLIST.md Pre-submission quality checklist

Tips for Medical Imaging Review

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
  • • It is part of a pack with 26 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Medical Imaging Review

What does the Medical Imaging Review skill do?

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 medic

How do I install Medical Imaging Review?

Run "npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill medical-imaging-review" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Medical Imaging Review work in Cursor and Codex?

Yes. Medical Imaging Review uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Medical Imaging Review free?

Medical Imaging Review is open source on GitHub. It is free to install; check the license before commercial use.

Who made Medical Imaging Review?

Medical Imaging Review is published by brycewang-stanford in the brycewang-stanford/Auto-Empirical-Research-Skills repository, together with 25 other skills.

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