Khairul Salleh Basaruddin
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Preferred name
Khairul Salleh Basaruddin
Official Name
Basaruddin, Khairul Salleh
Alternative Name
Basaruddin, Khairul S.
Basaruddin, K
Bin Basaruddin, Khairul Salleh
Basaruddin, K. S.
Khairul, Salleh B.
Main Affiliation
Scopus Author ID
54683507500
Researcher ID
I-8478-2019

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  • Publication
    Supervised machine learning to predict drilling temperature of bone
    (MDPI, 2024)
    Md Ashequl Islam
    ;
    Nur Saifullah Bin Kamarrudin
    ;
    Muhammad Farzik Ijaz
    ;
    Ruslizam Daud
    ;
    Abdulnasser Nabil Abdullah
    ;
    Khairul Salleh Basaruddin
    ;
    Hiroshi Takemura
    Surgeons face a significant challenge due to the heat generated during drilling, as excessive temperatures at the bone–tool interface can lead to irreversible damage to the regenerative soft tissue and result in thermal osteonecrosis. While previous studies have explored the use of machine learning to predict the temperature rise during bone drilling, this in vitro study introduces a comprehensive approach by combining the Response Surface Methodology (RSM) with advanced machine learning techniques. The main objective lies in the comprehensive evaluation and comparison of support vector machine (SVM) and random forest (RF) models specifically for the optimization of the bone drilling parameters to prevent thermal bone necrosis. A total of 27 experiments were conducted using a multi-level factorial method, with analysis performed via the Minitab software version 19.1. Performance metrics such as the mean squared error (MSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were used to assess model accuracy. The RF model emerged as the most effective, with R2 values of 94.2% for testing and 97.3% for training data, significantly outperforming other models in predicting temperature fluctuations. This study demonstrates the superior predictive capabilities of the RF model and offers a robust framework for the optimization of surgical procedures to mitigate the risk of thermal damage.
  • Publication
    Stability Analysis of Plate—Screw Fixation for Femoral Midshaft Fractures
    ( 2023)
    Izzawati Basirom
    ;
    Ruslizam Daud
    ;
    Muhammad Farzik Ijaz
    ;
    Mohd Afendi Rojan
    ;
    Khairul Salleh Basaruddin
    An understanding of the biomechanical characteristics and configuration of flexible and locked plating in order to provide balance stability and flexibility of implant fixation will help to construct and promote fast bone healing. The relationship between applied loading and implantation configuration for best bone healing is still under debate. This study aims to investigate the relationship between implant strength, working length, and interfragmentary strain (εIFM) on implant stability for femoral midshaft transverse fractures. The transverse fracture was fixed with a fragment locking compression plate (LCP) system. Finite element analysis was performed and subsequently characterised based on compression loading (600 N up to 900 N) and screw designs (conventional and locking) with different penetration depths (unicortical and bicortical). Strain theory was used to evaluate the stability of the model. The correlation of screw configuration with screw type shows a unicortical depth for both types (p < 0.01) for 700 N and 800 N loads and (p < 0.05) for configurations 134 and 124. Interfragmentary strain affected only the 600 N load (p < 0.01) for the bicortical conventional type (group BC), and the screw configurations that were influenced were 1234 and 123 (p < 0.05). The low steepness of the slope indicates the least εIFM for the corresponding biomechanical characteristic in good-quality stability. A strain value of ≤2% promotes callus formation and is classified as absolute stability, which is the minimum required value for the induction of callus and the maximum value that allows bony bridging. The outcomes have provided the correlation of screw configuration in femoral midshaft transverse fracture implantation which is important to promote essential primary stability.
      2
  • Publication
    Soft material drilling: a thermo-mechanical analysis of polyurethane foam for biomimetic bone scaffolds and optimization of process parameters using Taguchi method
    (Cell Press, 2024)
    Md Ashequl Islam
    ;
    Nur Saifullah Kamarrudin
    ;
    Muhammad Farzik Ijaz
    ;
    Tatsuya Furuki
    ;
    Khairul Salleh Basaruddin
    ;
    Ruslizam Daud
    Drilling is a widely employed technique in machining processes, crucial for efficient material removal. However, when applied to living tissues, its invasiveness must be carefully considered. This study investigates drilling processes on polyurethane foam blocks mimicking human bone mechanical properties. Various drill bit types (118° twist, 135° twist, spherical, and conical), drilling speeds (1000–1600 rpm), and feed rates (20–80 mm/min) were examined to assess temperature elevation during drilling. The Taguchi method facilitated systematic experiment design and optimization. Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) identified significant drilling parameters affecting temperature rise. Validation was conducted through confirmation testing. Results indicate that standard twist drill bits with smaller point angles, lower drilling speeds, and higher feed rates effectively minimize temperature elevation during drilling