Machine Learning-Based Quantification of Vesicoureteral Reflux with Enhancing Accuracy and Efficiency
DOI:
https://doi.org/10.56294/dm2025756Keywords:
Vesicoureteral reflux (VUR), Voiding cystourethrogram (VCUG), Machine learning (ML), Objective grading, Radiographic evaluation, Pediatric urologyAbstract
Vesicoureteral reflux (VUR) is traditionally assessed using subjective grading systems, leading to variability in diagnosis. This study explores the potential of machine learning to enhance diagnostic accuracy by analysing voiding cystourethrogram (VCUG) images. The objective is to develop predictive models that provide an objective and consistent approach to VUR classification. A total of 113 VCUG images were reviewed, with experts grading them based on VUR severity. Nine distinct image features were selected to build six predictive models, which were evaluated using 'leave-one-out' cross-validation. The analysis identified renal calyces’ deformation patterns as key indicators of high-grade VUR. The models—Logistic Regression, Tree, Gradient Boosting, Neural Network, and Stochastic Gradient Descent—achieved precise classifications with no false positives or negatives. High sensitivity to subtle patterns characteristic of different VUR grades was confirmed by substantial Area Under the Curve (AUC) values. This study demonstrates that machine learning can address the limitations of subjective VUR assessments, offering a more reliable and standardized grading system. The findings highlight the significance of renal calyces’ deformation as a predictor of severe VUR cases. Future research should focus on refining methodologies, exploring additional image features, and expanding the dataset to enhance model accuracy and clinical applicability.
References
1. Al-Batah M, Salem Alzboon M, Alqaraleh M. Superior Classification of Brain Cancer Types Through Machine Learning Techniques Applied to Magnetic Resonance Imaging. Data Metadata [Internet]. 2025 Jan 1;4:472. Available from: https://dm.ageditor.ar/index.php/dm/article/view/472
2. Subhi Al-Batah M, Alqaraleh M, Salem Alzboon M. Improving Oral Cancer Outcomes Through Machine Learning and Dimensionality Reduction. Data Metadata [Internet]. 2025 Jan 2;3. Available from: https://dm.ageditor.ar/index.php/dm/article/view/570
3. Abdel Wahed M, Alqaraleh M, Salem Alzboon M, Subhi Al-Batah M. Application of Artificial Intelligence for Diagnosing Tumors in the Female Reproductive System: A Systematic Review. Multidiscip [Internet]. 2025 Jan 1;3:54. Available from: https://multidisciplinar.ageditor.uy/index.php/multidisciplinar/article/view/54
4. Alzboon MS, Alqaraleh M, Al-Batah MS. Diabetes Prediction and Management Using Machine Learning Approaches. Data Metadata [Internet]. 2025; Available from: https://doi.org/10.56294/dm2025545
5. Wahed MA, Alqaraleh M, Salem Alzboon M, Subhi Al-Batah M. Evaluating AI and Machine Learning Models in Breast Cancer Detection: A Review of Convolutional Neural Networks (CNN) and Global Research Trends. LatIA [Internet]. 2025 Jan;3:117. Available from: https://latia.ageditor.uy/index.php/latia/article/view/117
6. Wahed MA, Alqaraleh M, Alzboon MS, Subhi Al-Batah M. AI Rx: Revolutionizing Healthcare Through Intelligence, Innovation, and Ethics. Semin Med Writ Educ [Internet]. 2025 Jan;4:35. Available from: https://mw.ageditor.ar/index.php/mw/article/view/35
7. Alqaraleh M, Salem Alzboon M, Subhi Al-Batah M. Real-Time UAV Recognition Through Advanced Machine Learning for Enhanced Military Surveillance. Gamification Augment Real [Internet]. 2025 Jan;3:63. Available from: https://gr.ageditor.ar/index.php/gr/article/view/63
8. Alqaraleh M, Salem Alzboon M, Mohammad SA-B. Optimizing Resource Discovery in Grid Computing: A Hierarchical and Weighted Approach with Behavioral Modeling. LatIA [Internet]. 2025 Jan;3:97. Available from: https://latia.ageditor.uy/index.php/latia/article/view/97
9. Alzboon MS, Subhi Al-Batah M, Alqaraleh M, Alzboon F, Alzboon L. Phishing Website Detection Using Machine Learning. Gamification Augment Real [Internet]. 2025 Jan;3:81. Available from: http://dx.doi.org/10.56294/gr202581
10. Alqaraleh M, Salem Alzboon M, Subhi Al-Batah M, Solayman Migdadi H. From Complexity to Clarity: Improving Microarray Classification with Correlation-Based Feature Selection. LatIA [Internet]. 2025 Jan 1;3:84. Available from: https://latia.ageditor.uy/index.php/latia/article/view/84
11. Salem Alzboon M, Subhi Al-Batah M, Alqaraleh M, Alzboon F, Alzboon L. Guardians of the Web: Harnessing Machine Learning to Combat Phishing Attacks. Gamification Augment Real [Internet]. 2025 Jan;3:91. Available from: http://dx.doi.org/10.56294/gr202591
12. Alqaraleh M, Al-Batah M, Salem Alzboon M, Alzaghoul E. Automated quantification of vesicoureteral reflux using machine learning with advancing diagnostic precision. Data Metadata. 2025;4:460.
13. Wahed MA, Alqaraleh M, Alzboon MS, Al-Batah MS. Application of Artificial Intelligence for Diagnosing Tumors in the Female Reproductive System: A Systematic Review. Multidiscip. 2025;3:54.
14. Subhi Al-Batah M, Alzboon M, Alqaraleh M. Optimizing Genetic Algorithms with Multilayer Perceptron Networks for Enhancing TinyFace Recognition. Data Metadata [Internet]. 2024 Dec 30;3. Available from: https://dm.ageditor.ar/index.php/dm/article/view/594
15. Alzboon MS, Al-Shorman HM, Alka’awneh SMN, Saatchi SG, Alqaraleh MKS, Samara EIM, et al. The Role of Perceived Trust in Embracing Artificial Intelligence Technologies: Insights from Jordan’s SME Sector. In: Studies in Computational Intelligence [Internet]. 2024. p. 1–15. Available from: https://link.springer.com/10.1007/978-3-031-74220-0_1
16. Alzboon MS, Al-Shorman HM, Alka’awneh SMN, Saatchi SG, Alqaraleh MKS, Samara EIM, et al. The Role of Perceived Trust in Embracing Artificial Intelligence Technologies: Insights from Jordan’s SME Sector. In: Studies in Computational Intelligence [Internet]. Springer Nature Switzerland; 2024. p. 1–15. Available from: http://dx.doi.org/10.1007/978-3-031-74220-0_1
17. Muhyeeddin A, Mowafaq SA, Al-Batah MS, Mutaz AW. Advancing Medical Image Analysis: The Role of Adaptive Optimization Techniques in Enhancing COVID-19 Detection, Lung Infection, and Tumor Segmentation. LatIA [Internet]. 2024 Sep;2(74):74. Available from: https://latia.ageditor.uy/index.php/latia/article/view/74
18. Alqaraleh M. Enhanced Resource Discovery Algorithm for Efficient Grid Computing. In: Proceedings of the 3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024. 2024. p. 925–31.
19. Mowafaq SA, Alqaraleh M, Al-Batah MS. AI in the Sky: Developing Real-Time UAV Recognition Systems to Enhance Military Security. Data Metadata. 2024;3.
20. Al-Batah M, Salem Alzboon M, Alqaraleh M, Ahmad Alzaghoul F. Comparative Analysis of Advanced Data Mining Methods for Enhancing Medical Diagnosis and Prognosis. Data Metadata. 2024;3.
21. Alqaraleh M, Alzboon MS, Al-Batah MS. Skywatch: Advanced Machine Learning Techniques for Distinguishing UAVs from Birds in Airspace Security. Int J Adv Comput Sci Appl. 2024;15(11):1065–78.
22. Abdel Wahed M, Al-Batah M, Salem Alzboon M, Fuad Bader A, Alqaraleh M. Technological Innovations in Autonomous Vehicles: A Focus on Sensor Fusion and Environmental Perception. 2024 7th International Conference on Internet Applications, Protocols, and Services, NETAPPS 2024. 2024.
23. Wahed MA, Alzboon MS, Alqaraleh M, Ayman J, Al-Batah M, Bader AF. Automating Web Data Collection: Challenges, Solutions, and Python-Based Strategies for Effective Web Scraping. In: 2024 7th International Conference on Internet Applications, Protocols, and Services, NETAPPS 2024. 2024.
24. Wahed MA, Alzboon MS, Alqaraleh M, Halasa A, Al-Batah M, Bader AF. Comprehensive Assessment of Cybersecurity Measures: Evaluating Incident Response, AI Integration, and Emerging Threats. In: 2024 7th International Conference on Internet Applications, Protocols, and Services, NETAPPS 2024. 2024.
25. Alqaraleh M, Alzboon MS, Al-Batah MS, Wahed MA, Abuashour A, Alsmadi FH. Harnessing Machine Learning for Quantifying Vesicoureteral Reflux: A Promising Approach for Objective Assessment. Int J online Biomed Eng. 2024;20(11):123–45.
26. Al-Batah MS, Alzboon MS, Alzyoud M, Al-Shanableh N. Enhancing Image Cryptography Performance with Block Left Rotation Operations. Appl Comput Intell Soft Comput. 2024;2024(1):3641927.
27. Al-Shanableh N, Alzyoud M, Al-Husban RY, Alshanableh NM, Al-Oun A, Al-Batah MS, et al. Advanced ensemble machine learning techniques for optimizing diabetes mellitus prognostication: A detailed examination of hospital data. Data Metadata. 2024;3:363.
28. Al-Batah MS, Salem Alzboon M, Solayman Migdadi H, Alkhasawneh M, Alqaraleh M. Advanced Landslide Detection Using Machine Learning and Remote Sensing Data. Data Metadata [Internet]. 2024 Oct;1. Available from: https://dm.ageditor.ar/index.php/dm/article/view/419/782
29. Alqaraleh M. Enhancing Internet-based Resource Discovery: The Efficacy of Distributed Quadtree Overlay. In: Proceedings of the 3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024. 2024. p. 1619–28.
30. Alzboon MS, Alqaraleh M, Wahed MA, Alourani A, Bader AF, Al-Batah M. AI-Driven UAV Distinction: Leveraging Advanced Machine Learning. In: 2024 7th International Conference on Internet Applications, Protocols, and Services (NETAPPS) [Internet]. IEEE; 2024. p. 1–7. Available from: http://dx.doi.org/10.1109/netapps63333.2024.10823488
31. Wahed MA, Alzboon MS, Alqaraleh M, Al-Batah M, Bader AF, Wahed SA. Enhancing Diagnostic Precision in Pediatric Urology: Machine Learning Models for Automated Grading of Vesicoureteral Reflux. In: 2024 7th International Conference on Internet Applications, Protocols, and Services, NETAPPS 2024 [Internet]. IEEE; 2024. p. 1–7. Available from: http://dx.doi.org/10.1109/netapps63333.2024.10823509
32. Abuashour A, Salem Alzboon M, Kamel Alqaraleh M, Abuashour A. Comparative Study of Classification Mechanisms of Machine Learning on Multiple Data Mining Tool Kits. Am J Biomed Sci Res 2024 [Internet]. 2024;22(1):1. Available from: www.biomedgrid.com
33. Alqaraleh M, Subhi Al-Batah M, Salem Alzboon M, Alzboon F, Alzboon L, Nayef Alamoush M. From Puffs to Predictions: Leveraging AI, Wearables, and Biomolecular Signatures to Decode Smoking’s Multidimensional Impact on Cardiovascular Health. Semin Med Writ Educ [Internet]. 2024 Dec 30;3. Available from: https://doi.org/10.56294/mw2024.670
34. Alqaraleh M, Subhi Al-Batah M, Salem Alzboon M, Alzboon F, Alzboon L, Nayef Alamoush M. Echoes in the Genome: Smoking’s Epigenetic Fingerprints and Bidirectional Neurobiological Pathways in Addiction and Disease. Semin Med Writ Educ [Internet]. 2024 Dec 30;3. Available from: https://doi.org/10.56294/mw2024.585
35. Alqaraleh M, Alzboon MS, Al-Batah M, Saleh O, Migdadi HS, Elrashidi A, et al. Advanced Machine Learning Models for Real-Time Drone and Bird Differentiation in Aerial Surveillance Systems. In: 2024 25th International Arab Conference on Information Technology (ACIT) [Internet]. IEEE; 2024. p. 1–8. Available from: https://ieeexplore.ieee.org/document/10877066/
36. Alqaraleh M, Alzboon MS, Al-Batah M, Migdadi HS, Saleh O, Alazaidah R, et al. Innovative Machine Learning Solutions for Automated Kidney Tumor Detection in CT Imaging Through Comparative Analysis. In: 2024 25th International Arab Conference on Information Technology (ACIT) [Internet]. IEEE; 2024. p. 1–9. Available from: https://ieeexplore.ieee.org/document/10876924/
37. Alrjoob HM, Alazaidah R, Batyha R, Khafajeh H, Elsoud EA, Saeb Al-Sherideh A, et al. Classifying Psychiatric Patients Using Machine Learning. In: 2024 25th International Arab Conference on Information Technology (ACIT) [Internet]. IEEE; 2024. p. 1–9. Available from: https://ieeexplore.ieee.org/document/10877074/
38. Alazaidah R, Samara G, Katrawi A, Hadi W, Al-Safarini MY, Al-Mamoori F, et al. Prediction of Hypertension Disease Using Machine Learning Techniques: Case Study from Jordan. In: 2024 25th International Arab Conference on Information Technology (ACIT) [Internet]. IEEE; 2024. p. 1–6. Available from: https://ieeexplore.ieee.org/document/10877088/
39. Alzboon MS, Qawasmeh S, Alqaraleh M, Abuashour A, Bader AF, Al-Batah M. Machine Learning Classification Algorithms for Accurate Breast Cancer Diagnosis. In: 2023 3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023. 2023.
40. Alzboon MS, Qawasmeh S, Alqaraleh M, Abuashour A, Bader AF, Al-Batah M. Pushing the Envelope: Investigating the Potential and Limitations of ChatGPT and Artificial Intelligence in Advancing Computer Science Research. In: 2023 3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023. 2023.
41. Alzboon MS, Al-Batah M, Alqaraleh M, Abuashour A, Bader AF. A Comparative Study of Machine Learning Techniques for Early Prediction of Prostate Cancer. In: 2023 IEEE 10th International Conference on Communications and Networking, ComNet 2023 - Proceedings. 2023.
42. Alzboon MS, Bader AF, Abuashour A, Alqaraleh MK, Zaqaibeh B, Al-Batah M. The Two Sides of AI in Cybersecurity: Opportunities and Challenges. In: Proceedings of 2023 2nd International Conference on Intelligent Computing and Next Generation Networks, ICNGN 2023. 2023.
43. Alzboon MS, Al-Batah MS, Alqaraleh M, Abuashour A, Bader AFH. Early Diagnosis of Diabetes: A Comparison of Machine Learning Methods. Int J online Biomed Eng. 2023;19(15):144–65.
44. Alzboon MS, Al-Batah M, Alqaraleh M, Abuashour A, Bader AF. A Comparative Study of Machine Learning Techniques for Early Prediction of Diabetes. In: 2023 IEEE 10th International Conference on Communications and Networking, ComNet 2023 - Proceedings. 2023. p. 1–12.
45. Alzboon MS, Al-Batah MS. Prostate Cancer Detection and Analysis using Advanced Machine Learning. Int J Adv Comput Sci Appl. 2023;14(8):388–96.
46. Al-Batah MS, Alzboon MS, Alazaidah R. Intelligent Heart Disease Prediction System with Applications in Jordanian Hospitals. Int J Adv Comput Sci Appl. 2023;14(9):508–17.
47. Putri AK, Alzboon MS. Doctor Adam Talib’s Public Relations Strategy in Improving the Quality of Patient Service. Sinergi Int J Commun Sci. 2023;1(1):42–54.
48. Alzboon M. Semantic Text Analysis on Social Networks and Data Processing: Review and Future Directions. Inf Sci Lett. 2022;11(5):1371–84.
49. Alzboon MS. Survey on Patient Health Monitoring System Based on Internet of Things. Inf Sci Lett. 2022;11(4):1183–90.
50. Alzboon MS, Aljarrah E, Alqaraleh M, Alomari SA. Nodexl Tool for Social Network Analysis. Turkish J Comput Math Educ. 2021;12(14):202–16.
51. Alomari SA, Alqaraleh M, Aljarrah E, Alzboon MS. Toward achieving self-resource discovery in distributed systems based on distributed quadtree. J Theor Appl Inf Technol. 2020;98(20):3088–99.
52. Alzboon MS, Mahmuddin M, Arif S. Resource discovery mechanisms in shared computing infrastructure: A survey. In: Advances in Intelligent Systems and Computing. 2020. p. 545–56.
53. Alomari SA, Alzboon MS, Al-Batah MS, Zaqaibeh B. A novel adaptive schema to facilitates playback switching technique for video delivery in dense LTE cellular heterogeneous network environments. Int J Electr Comput Eng [Internet]. 2020 Oct;10(5):5347–67. Available from: http://ijece.iaescore.com/index.php/IJECE/article/view/16563
54. Alomari SA, Salaimeh S Al, Jarrah E Al, Alzboon MS. Enhanced logistics information service systems performance: using theoretical model and cybernetics’ principles. WSEAS Trans Bus Econ [Internet]. 2020 Apr;17:278–87. Available from: https://wseas.com/journals/bae/2020/a585107-896.pdf
55. Alomari, Alzboon, Zaqaibeh, Al-Batah, Saleh Ali, Mowafaq Salem, Belal MS. An Effective Self-Adaptive Policy for Optimal Video Quality over Heterogeneous Mobile Devices and Network Discovery Services. Appl Math Inf Sci [Internet]. 2019 May;13(3):489–505. Available from: http://www.naturalspublishing.com/Article.asp?ArtcID=19739
56. Al Tal S, Al Salaimeh S, Ali Alomari S, Alqaraleh M. The modern hosting computing systems for small and medium businesses. Acad Entrep J. 2019;25(4):1–7.
57. Al-Batah M, Zaqaibeh B, Alomari SA, Alzboon MS. Gene Microarray Cancer classification using correlation based feature selection algorithm and rules classifiers. Int J online Biomed Eng. 2019;15(8):62–73.
58. Alzboon MS. Internet of things between reality or a wishing - list : a survey. Int J Eng Technol. 2019;7(June):956–61.
59. Mandis M, Chebeir JA, Baratti R, Romagnoli JA, Tronci S. Machine learning for monitoring and control of NGL recovery plants. Chem Eng Trans. 2021;86:997–1002.
60. Murdaca G, Caprioli S, Tonacci A, Billeci L, Greco M, Negrini S, et al. A Machine Learning Application to Predict Early Lung Involvement in Scleroderma: A Feasibility Evaluation. Diagnostics [Internet]. 2021 Oct 12;11(10):1880. Available from: https://www.mdpi.com/2075-4418/11/10/1880
61. Tomlinson E, Flaherty A, Akhbari B, Weaver B, Waryasz GR, Guss D, et al. Determining the Key Predictive Factors for Non-Union in Fifth Metatarsal Fractures: A Machine Learning-Based Study. Foot Ankle Orthop [Internet]. 2022 Oct 21;7(4):2473011421S. Available from: https://journals.sagepub.com/doi/10.1177/2473011421S00974
62. Emile SH, Ghareeb W, Elfeki H, Sorogy M El, Fouad A, Elrefai M. Development and Validation of an Artificial Intelligence-Based Model to Predict Gastroesophageal Reflux Disease After Sleeve Gastrectomy. Obes Surg. 2022;32(8):2537–47.
63. Satyanarayan A, Peters CA. Advances in robotic surgery for pediatric ureteropelvic junction obstruction and vesicoureteral reflux: history, present, and future. World J Urol. 2020;38(8):1821–6.
64. Gurumoorthy G, Vaidyanathan SG. Gastric Disorder Analysis Using Hybrid Optimization with Machine Learning. J Biomater Tissue Eng. 2023;13(3):453–62.
65. Lee KS, Song IS, Kim ES, Kim HI, Ahn KH. Association of preterm birth with medications: machine learning analysis using national health insurance data. Arch Gynecol Obs. 2022;305(5):1369–76.
66. Lee KS, Kim ES, Kim DY, Song IS, Ahn KH. Association of Gastroesophageal Reflux Disease with Preterm Birth: Machine Learning Analysis. J Korean Med Sci. 2021;36(43).
67. Lin PH, Hsieh J-G, Wu P-C, Yu H-C, Jeng J-H. Machine Learning Approach for Risk Prediction of Erosive Esophagitis in a Health Check-up Population in Taiwan. In: 2021 IEEE 3rd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) [Internet]. IEEE; 2021. p. 208–10. Available from: https://ieeexplore.ieee.org/document/9510751/
68. Lee M-J, Kim J-Y, Kim P, Lee I-S, Mswahili ME, Jeong Y-S, et al. Novel Cocrystals of Vonoprazan: Machine Learning-Assisted Discovery. Pharmaceutics [Internet]. 2022 Feb 16;14(2):429. Available from: https://www.mdpi.com/1999-4923/14/2/429
69. Hozawa S, Maeda S, Kikuchi A, Koinuma M. Exploratory research on asthma exacerbation risk factors using the Japanese claims database and machine learning: a retrospective cohort study. J Asthma [Internet]. 2022 Jul 3;59(7):1328–37. Available from: https://www.tandfonline.com/doi/full/10.1080/02770903.2021.1923740
70. Bauschard M, Maizels M, Kirsch A, Koyle M, Chaviano T, Liu D, et al. Computer-Enhanced Visual Learning Method to Teach Endoscopic Correction of Vesicoureteral Reflux: An Invitation to Residency Training Programs to Utilize the CEVL Method. Adv Urol [Internet]. 2012;2012:1–8. Available from: http://www.hindawi.com/journals/au/2012/831384/
71. Escolino M, others. Endoscopic injection of bulking agents in pediatric vesicoureteral reflux: a narrative review of the literature. Pediatr Surg Int. 2023;39(1).
72. Ergün O, Serel TA, Öztürk SA, Serel HB, Soyupek S, Hoşcan B. Deep-learning-based diagnosis and grading of vesicoureteral reflux: A novel approach for improved clinical decision-making. J Surg Med [Internet]. 2024 Jan 17;8(1):12–6. Available from: https://jsurgmed.com/article/view/8020
73. Simicic Majce A, Arapovic A, Saraga-Babic M, Vukojevic K, Benzon B, Punda A, et al. Intrarenal Reflux in the Light of Contrast-Enhanced Voiding Urosonography. Front Pediatr [Internet]. 2021 Mar 2;9. Available from: https://www.frontiersin.org/articles/10.3389/fped.2021.642077/full
74. Lee AM, Hu J, Xu Y, Abraham AG, Xiao R, Coresh J, et al. Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology. J Am Soc Nephrol [Internet]. 2022 Feb;33(2):375–86. Available from: https://journals.lww.com/10.1681/ASN.2021040538
75. Banikhalaf M, Alomari SA, Alzboon MS. An advanced emergency warning message scheme based on vehicles speed and traffic densities. Int J Adv Comput Sci Appl. 2019;10(5):201–5.
76. Arif S, Alzboon MS, Mahmuddin M. Distributed quadtree overlay for resource discovery in shared computing infrastructure. Adv Sci Lett. 2017;23(6):5397–401.
77. Mahmuddin M, Alzboon MS, Arif S. Dynamic network topology for resource discovery in shared computing infrastructure. Adv Sci Lett. 2017;23(6):5402–5.
78. Alzboon MS, Alomari S, Al-Batah MS, Alomari SA, Banikhalaf M. The characteristics of the green internet of things and big data in building safer, smarter, and sustainable cities Vehicle Detection and Tracking for Aerial Surveillance Videos View project Evaluation of Knowledge Quality in the E-Learning System View pr [Internet]. Vol. 6, Article in International Journal of Engineering and Technology. 2017. p. 83–92. Available from: https://www.researchgate.net/publication/333808921
79. Mowafaq Salem Alzboon M. Mahmuddin ASCA. Challenges and Mitigation Techniques of Grid Resource Management System. In: National Workshop on FUTURE INTERNET RESEARCH (FIRES2016). 2016. p. 1–6.
80. Al-Batah MS, Al-Eiadeh MR. An improved discreet Jaya optimisation algorithm with mutation operator and opposition-based learning to solve the 0-1 knapsack problem. Int J Math Oper Res. 2023;26(2):143-69.
81. Al-Batah MS. Testing the probability of heart disease using classification and regression tree model. Annu Res Rev Biol. 2014;4(11):1713-25.
82. Alzboon MS, Arif AS, Mahmuddin M. Towards self-resource discovery and selection models in grid computing. ARPN J Eng Appl Sci. 2016;11(10):6269–74.
83. Al-Batah MS. Modified recursive least squares algorithm to train the hybrid multilayered perceptron (HMLP) network. Appl Soft Comput. 2010;10(1):236-44.
84. Alzboon MS, Sintok UUM, Sintok UUM, Arif S. Towards Self-Organizing Infrastructure : A New Architecture for Autonomic Green Cloud Data Centers. ARPN J Eng Appl Sci. 2015;1–7.
85. Al-Batah MS, Al-Eiadeh MR. An improved binary crow-JAYA optimisation system with various evolution operators, such as mutation for finding the max clique in the dense graph. Int J Comput Sci Math. 2024;19(4):327-38.
86. Al-Batah MS. Ranked features selection with MSBRG algorithm and rules classifiers for cervical cancer. Int J Online Biomed Eng. 2019;15(12):4.
87. SalemAlzboon, Mowafaq and Arif, Suki and Mahmuddin, M and Dakkak O. Peer to Peer Resource Discovery Mechanisms in Grid Computing : A Critical Review. In: The 4th International Conference on Internet Applications, Protocols and Services (NETAPPS2015). 2015. p. 48–54.
88. Al-Batah MS. Integrating the principal component analysis with partial decision tree in microarray gene data. IJCSNS Int J Comput Sci Netw Secur. 2019;19(3):24-29.
89. Al-Oqily I, Alzboon M, Al-Shemery H, Alsarhan A. Towards autonomic overlay self-load balancing. In: 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013. Ieee; 2013. p. 1–6.
90. Kapoor S, Sharma A, Verma A, Dhull V, Goyal C. A Comparative Study on Deep Learning and Machine Learning Models for Human Action Recognition in Aerial Videos. Int Arab J Inf Technol [Internet]. 2023;20(4). Available from: https://iajit.org/upload/files/A-Comparative-Study-on-Deep-Learning-and-Machine-Learning-Models-for-Human-Action-Recognition-in-Aerial-Videos.pdf
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Copyright (c) 2025 Muhyeeddin Alqaraleh, Mowafaq Salem Alzboon, Mohammad Subhi Al-Batah, Lana Yasin Al Aesa, Mohammed Hasan Abu-Arqoub, Rashiq Rafiq Marie, Firas Hussein Alsmadi (Author)
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