About This Project

🎯 Purpose

AI4Sarcopenia Literature Daily is a dynamic literature review system that automatically monitors and organizes the latest research papers in AI-driven body shape analysis for sarcopenia. This project accompanies the academic paper:

“Literature Review of AI-Driven Body Shape Analysis for Sarcopenia”
Aizierjiang Aierislan, James Hahn
Institute for Innovation in Health Computing, The George Washington University

Unlike traditional static literature reviews, this system transforms the survey into a living document that automatically updates and expands its corpus of cited works daily as new relevant publications emerge.

📄 Abstract

Sarcopenia, a progressive skeletal muscle disorder contributing to frailty, disability, and mortality in aging populations, has become a growing focus of artificial intelligence (AI) research for improved diagnosis and assessment. This systematic review evaluates AI-driven body shape analysis for sarcopenia, encompassing both medical imaging-based body composition assessment and emerging 3D body surface scanning technologies.

By analyzing 962 studies from diverse scholarly databases (January 2015 onwards), our search strategy included terms spanning:

  • Medical imaging: CT, MRI, DXA, ultrasound
  • 3D body shape analysis: morphometry, computer graphics
  • AI/ML methods: deep learning, machine learning, computer vision

🔄 How It Works

  1. Automated Fetching: GitHub Actions runs every 24 hours to fetch new papers from arXiv
  2. Smart Categorization: Papers are organized into 12 sarcopenia-focused research domains
  3. Code Links: Automatically finds associated GitHub repositories via Papers with Code
  4. Web Display: Beautiful, searchable interface with sidebar navigation

📊 Research Coverage

We track papers across these key research areas based on the systematic search strategy:

Application Keywords (K_A)

  • sarcopenia, sarcopenic, sarcopenia obesity

Technology Keywords (K_T)

  • machine learning, deep learning, AI
  • computer vision, computer graphics
  • 3D body, morphometry, body shape

Purpose Keywords (K_P)

  • diagnos, detect, assess, predict, treat*

12 Research Domains

  1. Sarcopenia AI Detection - Core sarcopenia detection and diagnosis
  2. CT Body Composition - L3 vertebral level analysis, skeletal muscle index
  3. MRI Body Composition - Muscle analysis and fat quantification
  4. DXA & BIA Analysis - Appendicular lean mass, bioelectrical impedance
  5. Ultrasound Muscle Assessment - Point-of-care muscle assessment
  6. Deep Learning Segmentation - U-Net, CNN for medical imaging
  7. 3D Body Shape Analysis - Emerging area: optical body scanning, morphometry
  8. ML Risk Prediction - Random Forest, XGBoost for sarcopenia prediction
  9. Wearables & mHealth - Gait analysis, smartphone screening, SARC-F
  10. Explainable AI Healthcare - XAI, SHAP, interpretable models
  11. Aging & Muscle Health - EWGSOP/AWGS criteria, geriatric frailty
  12. Cancer & Cachexia - Oncology sarcopenia, chemotherapy body composition

🚀 Features

Automatic Updates

  • Updates every 24 hours via GitHub Actions
  • Fetches latest papers from arXiv API
  • Updates code repository links weekly

Smart Organization

  • 12 specialized sarcopenia research categories
  • 100+ carefully curated keywords from systematic review
  • Relevance-based filtering

User-Friendly Interface

  • Searchable paper database
  • Sidebar navigation for easy browsing
  • Responsive design for mobile/desktop

Open Source

  • Fully customizable configuration
  • Easy to fork and adapt
  • Documented codebase

🛠️ Technology Stack

  • Backend: Python, arXiv API
  • Frontend: Jekyll, GitHub Pages
  • Theme: Just the Docs (customized)
  • Automation: GitHub Actions
  • Deployment: GitHub Pages

📈 Statistics

  • 12 Sarcopenia-focused Research Domains
  • 100+ Curated Keywords
  • Daily Updates
  • 15 Papers per topic (configurable)

📖 Key References

The methodology follows standards from:

  • EWGSOP2: European Working Group on Sarcopenia in Older People
  • AWGS 2019: Asian Working Group for Sarcopenia
  • CASP: Critical Appraisal Skills Programme
  • AMSTAR 2: Assessment of Multiple Systematic Reviews

🤝 Contributing

Contributions are welcome! Ways to contribute:

  1. Add Keywords: Suggest new research topics
  2. Improve Filters: Refine search queries
  3. Report Issues: Found a bug? Let us know
  4. Documentation: Help improve guides

📄 License

This project is provided for research and educational purposes, under MIT license.

🙏 Acknowledgments

📧 Contact

  • Authors: Aizierjiang Aierislan
  • Institution: Institute for Innovation in Health Computing, The George Washington University
  • Email: mysoft@111.com
  • GitHub: @aizierjiang
  • Issues: Report here

Last updated: 2026-04-02

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Copyright © 2025 Aizierjiang Aierislan | Institute for Innovation in Health Computing, GWU | Updated daily via GitHub Actions. View on GitHub