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Related Concept Videos

Bone Structure01:55

Bone Structure

Within the skeletal system, the structure of a bone, or osseous tissue, can be exemplified in a long bone, like the femur, where there are two types of osseous tissue: cortical and cancellous.
Bone Remodeling01:40

Bone Remodeling

Bone remodeling is a continuous and balanced process of bone resorption by osteoclasts and bone formation by osteoblasts. In adults, it helps maintain bone mass and calcium homeostasis. While mechanical stress can stimulate turnover as part of the normal maintenance and reparative process, several hormones also regulate bone remodeling.
Classification of Bones01:18

Classification of Bones

The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The long...

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Using statistical modelling and machine learning in detecting bone properties: A systematic review protocol.

Osama Abdelhay1, Rand Alshoubaki1, Sana Murad1

  • 1Department of Data Science and Artificial Intelligence, Princess Sumaya University for Technology, Amman, Jordan.

Plos One
|March 11, 2025
PubMed
Summary

Artificial intelligence (AI) and machine learning (ML) show promise for improving osteoporosis detection. This systematic review will assess AI/ML tools for bone health, aiming for more accessible and accurate diagnostics.

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Area of Science:

  • Medical Imaging and Diagnostics
  • Artificial Intelligence in Healthcare
  • Bone Health Research

Background:

  • Osteoporosis is a major health concern characterized by reduced bone mass and increased fracture risk.
  • Traditional methods like Dual-energy X-ray Absorptiometry (DXA) have limitations in sensitivity and accessibility.
  • Emerging AI and ML tools offer potential for enhanced analysis of complex medical data for osteoporosis detection.

Purpose of the Study:

  • To systematically review and evaluate the application and effectiveness of AI and ML methods in detecting bone properties and osteoporosis.
  • To compare the performance of AI/ML models against traditional diagnostic methods.
  • To identify advancements and guide future research in AI/ML for bone health assessment.

Main Methods:

  • Systematic review following PRISMA-P guidelines.
  • Comprehensive literature search across major databases (PubMed, Embase, IEEE Xplore, Scopus, Cochrane Library, GitHub) until March 2025.
  • Inclusion of studies on adults (40+ years) using AI/ML for bone density or properties; dual reviewer screening, data extraction, and risk of bias assessment.
  • Data synthesis via narrative synthesis and meta-analysis using Review Manager and R software.

Main Results:

  • This section will be populated upon completion of the systematic review and data analysis.
  • Expected to identify and analyze various AI/ML models for osteoporosis detection.
  • Will compare the effectiveness of AI/ML with traditional diagnostic methods.

Conclusions:

  • AI and ML hold significant potential to revolutionize osteoporosis detection and prediction.
  • Findings will inform healthcare professionals, researchers, and policymakers on AI/ML advancements in bone health.
  • This review aims to facilitate the integration of AI/ML tools into routine osteoporosis screening and management.