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Related Concept Videos

Knee Joint01:23

Knee Joint

1.3K
The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...
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Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint
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Can Artificial Intelligence Diagnose Knee Osteoarthritis?

Mihir Tandon1, Nitin Chetla2, Adarsh Mallepally3

  • 1Albany Medical College, Albany, NY, United States.

JMIR Biomedical Engineering
|April 23, 2025
PubMed
Summary

GPT-4o shows promise in identifying knee osteoarthritis but requires caution. While sensitive, its specificity is low, necessitating careful use in clinical image analysis.

Keywords:
ChatGPTGPT-4oX-rayslarge language modelmachine learningosteoarthritisosteoarthritis detectionradiology

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Area of Science:

  • Artificial Intelligence in Medicine
  • Medical Imaging Analysis
  • Orthopedics

Background:

  • Knee osteoarthritis (KO) is a prevalent degenerative joint disease.
  • Accurate diagnosis of KO is crucial for effective patient management.
  • AI tools are increasingly explored for medical image interpretation.

Purpose of the Study:

  • To evaluate the diagnostic performance of GPT-4o for knee osteoarthritis identification.
  • To assess the sensitivity and specificity of GPT-4o in detecting knee osteoarthritis from medical images.

Main Methods:

  • Analysis of GPT-4o's capability in identifying knee osteoarthritis.
  • Evaluation of model performance metrics including sensitivity and specificity.

Main Results:

  • GPT-4o demonstrated good sensitivity in identifying knee osteoarthritis.
  • The model exhibited poor specificity in diagnosing knee osteoarthritis.
  • Potential for AI in KO detection but limitations exist.

Conclusions:

  • GPT-4o shows potential for knee osteoarthritis detection but requires further refinement.
  • Clinicians and patients should exercise caution when utilizing GPT-4o for KO image analysis.
  • Future research should focus on improving the specificity of AI models for osteoarthritis diagnosis.