Deciphering Knee Osteoarthritis Diagnostic Features With Explainable Artificial Intelligence: A Systematic Review-Reference-Cited by-同舟云学术

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Deciphering Knee Osteoarthritis Diagnostic Features With Explainable Artificial Intelligence: A Systematic Review

Published:2024 Issue: Volume:12 Page:109080-109108
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Xin Teoh Yun¹^ORCID,Othmani Alice²^ORCID,Li Goh Siew³^ORCID,Usman Juliana¹,Lai Khin Wee¹^ORCID

Affiliation:

1. Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia

2. Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil, Vitry-sur-Seine, France

3. Sports and Exercise Medicine Research and Education Group, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia

Funder

Ministry of Higher Education, Malaysia

Universiti Malaya through the Fundamental Research Grant Scheme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10623535.pdf?arnumber=10623535

Reference126 articles.

1. Global, regional, and national burden of osteoarthritis, 1990–2020 and projections to 2050: a systematic analysis for the Global Burden of Disease Study 2021

2. Global, regional, and national trends in osteoarthritis disability-adjusted life years (DALYs) from 1990 to 2019: a comprehensive analysis of the global burden of disease study

3. The role of imaging in osteoarthritis

4. Assessment of discordance between radiologists and emergency physicians of RADIOgraphs among discharged patients in an emergency department: the RADIO-ED study

5. Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data

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