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  1. 1

    Region-growing based segmentation and bag of features classification for breast ultrasound images by Lee, Lay Khoon

    Published 2017
    “…In the next stage, which is the segmentation stage, region growing algorithm is used to automatically detect tumors in ultrasound images. …”
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  2. 2

    Observer-based fault detection with fuzzy variable gains and its application to industrial servo system by Eissa, Magdy Abdullah, Sali, Aduwati, Hassan, Mohd Khair, Bassiuny, A. M., Darwish, Rania R.

    Published 2020
    “…Also, a scoring algorithm has been implemented, to evaluate the classification ability of the algorithm and the early fault detection ability. …”
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    COMPUTER AIDED SYSTEM FOR BREAST CANCER DIAGNOSIS USING CURVELET TRANSFORM by MOHAMED ELTOUKHY, MOHAMED MESELHY

    Published 2011
    “…Subsequently, a region growing algorithm was used to locate the pectoral muscle and suppress it from the breast. …”
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  5. 5

    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…This study evaluated the use of insitu and remote sensors to early detect the Ganoderma infected oil palms before the visual symptoms are manifested (mildly infected). …”
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  6. 6

    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…This study concluded that for the early detection of BSR, a significant degree of accuracy was obtained. …”
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    Early diabetes risk prediction using Ant Colony Optimization algorithm / Nur Aisyatul Husna Ahmad Yusri and Rizauddin Saian by Ahmad Yusri, Nur Aisyatul Husna, Saian, Rizauddin

    Published 2023
    “…Therefore, this study has developed a classification model for predicting early diabetes risk using an Ant Colony Optimization (ACO) algorithm. …”
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  9. 9

    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

    Published 2023
    “…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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  10. 10

    An improved directed random walk framework for cancer classification using gene expression data by Seah, Choon Sen

    Published 2020
    “…It is found that these findings would improve the early diagnosis methods of cancer classification.…”
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  11. 11

    Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

    Published 2014
    “…The selected principal component scores were used in classification using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN) and Naive-Bayes (NB) multivariate classification algorithms. …”
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  12. 12

    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

    Published 2024
    “…Overall, the MCML classification algorithm is proven to be used as a benchmark for early detection of text-based mental health disorders.…”
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  13. 13

    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2021
    “…This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. …”
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  14. 14

    Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

    Published 2017
    “…To evaluate the algorithm, 350 samples for 10 types of Qira’at recitation are in used, and for justifying the best pattern classification, few algorithms are tested in the early preliminary evaluation with K-Nearest Neighbour, GMM and PPCA. …”
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  15. 15

    Using convolution neural networks for improving customer requirements classification performance of autonomous vehicle by Hao, Wang, Asrul, Adam, Fengrong, Han

    “…As the results, the accuracy of CNN classification has improved at least 6 percent compared to the conventional algorithms.…”
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  16. 16

    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…So that the study can have implications for cyber experts to be able to prevent malware attacks early. While further research requires a special algorithm to improve malware attack detection, in addition to KNN, SVM and Neural Network. …”
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    Diabetic Retinopathy Detection Model using Hybrid of U-Net and Vision Transformer Algorithms by Mudit, Khater

    Published 2024
    “…Now, we present a hybrid model which is a combination of U-Net algorithm used for image segmentation and Vision Transformer for classification. …”
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    Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.] by Suhaidin, Muhammad Iqbal, Mohamed Yusoff, Syarifah Adilah, Johan, Elly Johana, Mydin, Azlina, Wan Mohamad, Wan Anisha

    Published 2023
    “…This potential has been investigated by thoroughly compared with several other studies across implementation of different types of dataset and algorithms. Furthermore, additional prototypes could be used in clinical settings, providing valuable insights to healthcare providers and contributing to the advancement of medical research…”
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  20. 20

    Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Chong, Hou Ming, Yin Yap, Xien, Seng Chia, Kim

    Published 2023
    “…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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