Advances in Artificial Intelligence for automated knee osteoarthritis classification using the IKDC system.

Journal: European journal of orthopaedic surgery & traumatology : orthopedie traumatologie

Published Date: Dec 2, 2024

Abstract

INTRODUCTION: Knee osteoarthritis is one of the most prevalent and debilitating musculoskeletal diseases, with a high incidence among the elderly population. Early detection and accurate classification can improve clinical outcomes for affected patients.

Authors

Facundo Manuel Segura

Segura, Centro Privado de Ortopedia y Traumatología, 358 Justo Jose de Urquiza Street, X5000, Córdoba City, Córdoba, Argentina. facusegura@gmail.com.
Florencio Pablo Segura

Segura, Centro Privado de Ortopedia y Traumatología, 358 Justo Jose de Urquiza Street, X5000, Córdoba City, Córdoba, Argentina.
María Paz Lucero Zudaire

Instituto Modelo de Cardiología, 359 Sagrada Familia Av, X5000, Cordoba, Cordoba, Argentina.
Florencio Vicente Segura

Segura, Centro Privado de Ortopedia y Traumatología, 358 Justo Jose de Urquiza Street, X5000, Córdoba City, Córdoba, Argentina.

Keywords

Aged Artificial Intelligence Female Humans Machine Learning Male Middle Aged Osteoarthritis, Knee Radiography Sensitivity and Specificity Severity of Illness Index

External Resources

View on PubMed Access via DOI PubMed (39621063)

Advances in Artificial Intelligence for automated knee osteoarthritis classification using the IKDC system.

Abstract

Authors

Keywords

External Resources

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