3D Knee Kinematic Parameters Effectively Diagnose Knee Osteoarthritis and Assess Its Therapeutic Strategy. (20th March 2022)
- Record Type:
- Journal Article
- Title:
- 3D Knee Kinematic Parameters Effectively Diagnose Knee Osteoarthritis and Assess Its Therapeutic Strategy. (20th March 2022)
- Main Title:
- 3D Knee Kinematic Parameters Effectively Diagnose Knee Osteoarthritis and Assess Its Therapeutic Strategy
- Authors:
- Zeng, Xiaolong
Zhu, Ye
Xie, Zhenyan
Zhong, Guoqing
Huang, Wenhan
Ma, Limin
Zhang, Yu
Mao, Chuanbin - Abstract:
- Abstract : Knee osteoarthritis (KOA) is a worldwide disease leading to knee function loss and disorders. However, traditional assessment by X‐ray cannot assess patients' knee functions and disorders dynamically, making it impossible to achieve a direct functional assessment of KOA. To solve this problem, here it is shown that 3D knee gait parameters could be used to diagnose KOA and guide its therapeutic strategy through direct functional assessment. We employ a total of 1201 participants, and successfully build and validate diagnostic and predictive models for KOA diagnosis and therapeutic strategy using an artificial intelligence (AI)‐based method, logistic regression, a kind of interpretable machine learning. Four diagnostic models are successfully established including angular (AM), translational (TM), composite (CM), and ATCM (a parallel conjoint model of AM, TM, and CM) model with a Youden index of 0.7312, 0.6689, 0.8214, and 0.7492, respectively. The same AI‐based method is also used to develop medical decision classification (MDC) for predicting whether a KOA patient needs operative intervention or not. MDC has a Youden index, sensitivity, and specificity of 0.8886, 92.11%, and 96.75%, respectively. These findings contribute to new knowledge of knee kinematics and KOA diagnosis and represent a new approach to accurate KOA diagnosis and assessment. Abstract : The present study uses artificial intelligence (AI)‐based method, a kind of interpretable machine learning, toAbstract : Knee osteoarthritis (KOA) is a worldwide disease leading to knee function loss and disorders. However, traditional assessment by X‐ray cannot assess patients' knee functions and disorders dynamically, making it impossible to achieve a direct functional assessment of KOA. To solve this problem, here it is shown that 3D knee gait parameters could be used to diagnose KOA and guide its therapeutic strategy through direct functional assessment. We employ a total of 1201 participants, and successfully build and validate diagnostic and predictive models for KOA diagnosis and therapeutic strategy using an artificial intelligence (AI)‐based method, logistic regression, a kind of interpretable machine learning. Four diagnostic models are successfully established including angular (AM), translational (TM), composite (CM), and ATCM (a parallel conjoint model of AM, TM, and CM) model with a Youden index of 0.7312, 0.6689, 0.8214, and 0.7492, respectively. The same AI‐based method is also used to develop medical decision classification (MDC) for predicting whether a KOA patient needs operative intervention or not. MDC has a Youden index, sensitivity, and specificity of 0.8886, 92.11%, and 96.75%, respectively. These findings contribute to new knowledge of knee kinematics and KOA diagnosis and represent a new approach to accurate KOA diagnosis and assessment. Abstract : The present study uses artificial intelligence (AI)‐based method, a kind of interpretable machine learning, to discover the patterns of the characteristics of knee osteoarthritis from 3D gait data to set up diagnostic models for knee osteoarthritis (KOA). Furthermore, the study establishes a model to indicate whether the patients should be treated by conservative or operative therapy. … (more)
- Is Part Of:
- Advanced intelligent systems. Volume 4:Number 6(2022)
- Journal:
- Advanced intelligent systems
- Issue:
- Volume 4:Number 6(2022)
- Issue Display:
- Volume 4, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 4
- Issue:
- 6
- Issue Sort Value:
- 2022-0004-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-03-20
- Subjects:
- artificial intelligence -- diagnosis -- gait -- knee osteoarthritis -- medical decision classification
Artificial intelligence -- Periodicals
Robotics -- Periodicals
Control theory -- Periodicals
006.3 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
https://onlinelibrary.wiley.com/journal/26404567 ↗ - DOI:
- 10.1002/aisy.202100161 ↗
- Languages:
- English
- ISSNs:
- 2640-4567
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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- 22133.xml