Enterprise AI Analysis
Design and development of a model for tennis elbow injury prediction and prevention using Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) approaches
Lateral epicondylitis (tennis elbow) is a common sports injury posing diagnostic and management challenges. This study introduces a novel approach integrating Design of Experiments (DoE) with Response Surface Methodology (RSM) and an Expert System (ES) using Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for personalized injury prevention recommendations. This methodology empowers players with safer practices and aims to reduce incidence. Comprehensive education for athletes, coaches, and physicians is also emphasized for improved outcomes. The ANFIS approach achieved 99% accuracy for injury prediction, validated through multi-model prediction.
Executive Impact: Key Metrics at a Glance
Our analysis highlights the superior predictive capability of AI models in musculoskeletal disorder management. With ANFIS achieving an impressive 99% accuracy, this research demonstrates a significant advancement in early identification and personalized prevention of tennis elbow, offering actionable insights for athletes and medical professionals.
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ANFIS Prediction Accuracy
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ANN Correlation Coefficient
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ANFIS Mean Absolute Error
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ANFIS Root Mean Square Error
Deep Analysis & Enterprise Applications
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Enterprise Process Flow
Data Pre-processing
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Artificial Neural Network Design
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ANN Model Training and Validation
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Model Evaluation and Testing
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Expert System Development
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Validation and Conclusions
| Model | Key Factors Identified | Benefits |
|---|---|---|
| ANN | Flexion Angle, Elbow Torque, Elbow Strength |
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| FLS | Flexion Angle, Elbow Torque, Elbow Strength |
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| ANFIS | Flexion Angle, Elbow Torque, Elbow Strength |
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Injury Classification & MRI Mapping
The study categorizes tennis elbow injuries based on MRI findings, mapping clinical assessments to computational predictions.
- Mild Injury: Tendon thickening or thinning with increased internal signal intensity; the ligament appears thickened with intact structure and normal-to-increased signal. ANN Predicted Output: No or Low Injury Risk (0-0.3)
- Moderate Injury: Partial ligament tear, moderate edema, joint space narrowing. ANN Predicted Output: Moderate Injury Risk (0-0.6)
- Severe Injury: Complete ligament rupture, joint effusion, bone contusion. ANN Predicted Output: High Injury Risk (0.7-1.0)
99%
Prediction Accuracy Achieved by ANFIS
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Estimated Annual Savings
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Annual Hours Reclaimed
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