medical-imaging-review

luwill/research-skills · updated Apr 8, 2026

$npx skills add https://github.com/luwill/research-skills --skill medical-imaging-review
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summary

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

skill.md

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

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.753 reviews
  • Daniel Johnson· Dec 28, 2024

    I recommend medical-imaging-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aanya Yang· Dec 16, 2024

    Registry listing for medical-imaging-review matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aanya Chen· Dec 12, 2024

    Useful defaults in medical-imaging-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Dec 4, 2024

    medical-imaging-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Piyush G· Nov 23, 2024

    medical-imaging-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Layla Bhatia· Nov 19, 2024

    medical-imaging-review reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Sophia Chen· Nov 15, 2024

    medical-imaging-review has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Kofi Iyer· Nov 7, 2024

    Useful defaults in medical-imaging-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Nia Jain· Nov 3, 2024

    Registry listing for medical-imaging-review matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Meera Chawla· Oct 26, 2024

    I recommend medical-imaging-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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