The Master’s thesis defense of Haneen Saleh Hassan was held at the Department of Biomedical Engineering, College of Engineering, Al-Nahrain University. Her thesis was entitled:

“Biotribological Analysis of Hip Joint Using Artificial Intelligence”

The examination committee consisted of:

• Asst. Prof. Dr. Hassanein Ali Lafta – Chair
• Asst. Prof. Dr. Aseel Mohammed Ali Hussein – Member
• Dr. Omaima Raed Khairi – Member
• Prof. Dr. Sadiq Jaafar Abbas – Member and Supervisor

The study aimed to develop a reliable and interpretable artificial intelligence model for assessing and predicting the cumulative wear volume of an artificial hip joint over a five-year period. The significance of the research lies in integrating mechanical biotribological physics, such as wear and lubrication laws, with machine-learning algorithms to provide engineers, physicians, and surgeons with an accurate predictive tool for evaluating the service life of artificial joints and preventing early surgical failure.

The thesis presented a rigorous leakage-safe computational pipeline and reduced correlated physical variables, while comparing the performance of several algorithms, including Random Forest, Gradient Boosting, Support Vector Regression (SVR), and Linear Regression. The methodology was distinguished by the use of 5-Fold Nested Cross-Validation to ensure reliable clinical generalization. Split Conformal Prediction was also applied to provide 90% prediction intervals for each prediction.

In addition, SHAP and Permutation Importance techniques were employed to interpret the model outputs and determine the relative importance of each physical and clinical variable. Sobol indices and the Morris method were used to identify the most critical physical parameters influencing wear and lubrication rates.

The study results demonstrated the high efficiency of the proposed model in predicting wear-related outcomes, enhancing its potential for application in medical and engineering fields to support surgical decision-making and the design of artificial joints.

The thesis was accepted as it fulfilled the requirements for the award of a Master’s degree in Biomedical Engineering.