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  1. 1
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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  2. 2
    Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation

    Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation by Sivarao, Subramonian

    Published 2010
    “…The researchers conducted the prediction of C02 laser cut quality to obtain singleton output using machine learning techniques. …”
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  3. 3
    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining

    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

    Published 2009
    “…The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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  4. 4
    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network

    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

    Published 2009
    “…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
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  5. 5
    Automated transtibial prosthesis alignment: A systematic review

    Automated transtibial prosthesis alignment: A systematic review by Khamis T., Khamis A.A., Al Kouzbary M., Al Kouzbary H., Mokayed H., Razak N.A.A., Osman N.A.A.

    Published 2025
    “…The selected studies represent cutting-edge research, employing diverse approaches such as advanced machine learning algorithms and innovative alignment tools, to automate the detection and adjustment of prosthesis alignment. …”
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  6. 6
    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy

    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  7. 7
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  8. 8
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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  9. 9
    Covid-19 Fake News Detection Model On Social Media Data Using Machine Learning Techniques

    Covid-19 Fake News Detection Model On Social Media Data Using Machine Learning Techniques by Liew, Kelvin Kai Xuan

    Published 2023
    “…Finally, to categorise the covid -19 related dataset, multiple cutting-edge machine learning algorithms were trained. …”
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  10. 10
    Implementation of Health Monitoring System for Patients using Machine Learning Algorithms

    Implementation of Health Monitoring System for Patients using Machine Learning Algorithms by Hariprasad, U.S., UshaSree, R.

    Published 2024
    “…We employed the Decision Tree Algorithm to train and assess a model that produced a perfection of 66.66%.…”
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  11. 11
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  12. 12
    Brain stroke detection using medical images

    Brain stroke detection using medical images by Chew, Xin Ru

    Published 2025
    “…In order to enable automated brain clot detection and adapt to various image variations, machine learning algorithms are integrated for classification. …”
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  13. 13
    COVID-19 fake news detection model on social media data using machine learning techniques

    COVID-19 fake news detection model on social media data using machine learning techniques by Kai Xuan, Kelvin Liew, Bhuiyan, Mohaiminul Islam, Nur Shazwani, Kamarudin, Ahmad Fakhri, Ab Nasir, Muhammad Zulfahmi, Toh Abdullah@ Toh Chin Lai

    Published 2023
    “…Finally, to categorize the COVID -19 related dataset, multiple cutting-edge machine-learning algorithms were trained. …”
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  14. 14
    Credit Card Fraud Detection Using New Preprocessing And Hybrid Machine Learning Techniques

    Credit Card Fraud Detection Using New Preprocessing And Hybrid Machine Learning Techniques by Gasim, Esraa Faisal Malik

    Published 2023
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  15. 15
    An intelligent risk management framework for monitoring vehicular engine health

    An intelligent risk management framework for monitoring vehicular engine health by Rahim, Md. Abdur, Rahman, Md. Arafatur, Rahman, Md. Mustafizur, Zaman, Nafees, Moustafa, Nour, Razzak, Imran

    Published 2022
    “…The stacked ensemble of the deep learning algorithm outperformed other standard machine learning and deep learning algorithms in providing 80.3% decision accuracy for the 80% training data and efficiently managing large amounts of data. …”
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  16. 16
    Nanofluid heat transfer and machine learning: Insightful review of machine learning for nanofluid heat transfer enhancement in porous media and heat exchangers as sustainable and renewable energy solutions

    Nanofluid heat transfer and machine learning: Insightful review of machine learning for nanofluid heat transfer enhancement in porous media and heat exchangers as sustainable and r... by Riyadi T.W.B., Herawan S.G., Tirta A., Ee Y.J., Hananto A.L., Paristiawan P.A., Yusuf A.A., Venu H., Irianto, Veza I.

    Published 2025
    “…Nanofluid, coupled with machine learning, is at the forefront of cutting-edge research in sustainable and renewable energy sector. …”
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  17. 17
    Precognito: the emergence of blockchain & machine learning-based for student record authentication system

    Precognito: the emergence of blockchain & machine learning-based for student record authentication system by Murtaj, Sheikh Mohammad Tahsin, Mohammed, Mohammed, Abubakar Yusif, Abubakar, Yahya, Norzariyah, Abdulghafor, Rawad

    Published 2024
    “…This project aims to create a tool that combines two cutting-edge technologies, machine learning (ML) and blockchain, to combat problems like degree and transcript forgery. …”
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  18. 18
    Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate

    Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

    Published 2025
    “…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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  19. 19
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  20. 20
    Machine learning application in predicting anterior cruciate ligament injury among basketball players

    Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

    Published 2025
    “…A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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