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Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

Clinical Artificial Intelligence Applications: Musculoskeletal.

Simukayi Mutasa¹, Paul H Yi²

¹Department of Diagnostic Radiology, Division of Musculoskeletal Imaging, Thomas Jefferson University Medical Center, 111 South 11th Street, Third Floor, Philadelphia, PA 19107, USA.

Radiologic Clinics of North America

|October 25, 2021

Summary

This summary is machine-generated.

Artificial intelligence (AI) is transforming musculoskeletal imaging, offering current clinical applications and outlining future possibilities in the field.

Keywords:

Artificial intelligence Bone Clinical applications Deep learning Joint Machine learning Musculoskeletal Sports imaging

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Area of Science:

Radiology
Medical Imaging
Artificial Intelligence

Background:

Musculoskeletal imaging is crucial for diagnosing and managing a wide range of conditions.
Artificial intelligence (AI) is rapidly advancing and showing potential in medical image analysis.

Purpose of the Study:

To provide a comprehensive overview of current AI applications in clinical musculoskeletal imaging.
To explore potential future directions and emerging techniques for AI in this domain.

Main Methods:

Literature review of existing AI applications in musculoskeletal imaging.
Analysis of current trends and future research trajectories.

Main Results:

Current AI applications include image analysis, disease detection, and treatment planning.
Future applications may involve predictive modeling, personalized medicine, and enhanced image acquisition.

Conclusions:

AI holds significant promise for revolutionizing musculoskeletal imaging.
Continued research and development are essential to realize the full potential of AI in clinical practice.