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  1. 1
    Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population

    Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population by Yahaya, Yasmin Arijah Che

    Published 2023
    “…However, the Phenice age classification method is only applicable for sample age above 20 years old. …”
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  2. 2
    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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  3. 3
    BONE AGE ANALYSIS FROM BONE X-RAY

    BONE AGE ANALYSIS FROM BONE X-RAY by ABD GHANI, NOOR SYAZANA

    Published 2018
    “…To achieve the objectives, the bone age classification method will involve image segmentation of the x-ray, feature extraction from the segmented images and lastly, classification of bone age level. …”
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  4. 4
    An image-based children age range verification and classification based on facial features angle distribution and face shape elliptical ratio

    An image-based children age range verification and classification based on facial features angle distribution and face shape elliptical ratio by Razalli, Husniza, Rahmat, Rahmita Wirza O. K, Khalid, Fatimah, Sulaiman, Puteri Suhaiza

    Published 2017
    “…The angle that forms on human face images has been calculated based on selected facial features landmark points. The method was tested on FG-NET aging database. The classification of children from adults and the verification of children age range are implemented using SVM and Multi-SVM classification process. …”
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  5. 5
    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal

    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

    Published 2017
    “…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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  6. 6
    Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review

    Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review by Goh, Choon-Hian, Ferdowsi, Mahbuba, Gan, Ming Hong, Kwan, Ban-How, Lim, Wei Yin, Tee, Yee Kai, Rosli, Roshaslina, Tan, Maw Pin *

    Published 2024
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  7. 7
    Region-based segmentation and classification of Mandibular First Molar Tooth based on Demirjian’s method

    Region-based segmentation and classification of Mandibular First Molar Tooth based on Demirjian’s method by Norhasmira, Mohammad, M Y P M, Yusof, Rohana, Ahmad, Anuar Mikdad, Muad

    Published 2020
    “…A region-based segmentation method known as Watershed Transform associated with several image enhancement algorithms is implemented. …”
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  8. 8
    Virtual reality in algorithm programming course: practicality and implications for college students

    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
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  9. 9
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…To overcome such challenges, this study attempts to comprehend and improve the remote sensing technology for rooftop classification using the Worldview-3 (WV-3) image and object-based image analysis (OBIA) method. …”
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  10. 10
    A comparative analysis of machine learning algorithms for diabetes prediction

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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  11. 11
    An enhancement of age and gender classification accuracy with hybrid handcrafted and deep features using hierarchical extreme learning machine / Mohammad Javidan Darugar

    An enhancement of age and gender classification accuracy with hybrid handcrafted and deep features using hierarchical extreme learning machine / Mohammad Javidan Darugar by Mohammad Javidan , Darugar

    Published 2020
    “…Age and gender classification are some of the essential algorithms that have many use cases in our everyday life. …”
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  12. 12
    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud

    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

    Published 2023
    “…The best algorithm will not be the same for all the data sets. …”
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  13. 13
    Classification of transient facial wrinkle

    Classification of transient facial wrinkle by Rosdiyana, Samad, Mohammad Zarif, Rosli, Nor Rul Hasma, Abdullah, Mahfuzah, Mustafa, Dwi, Pebrianti, Nurul Hazlina, Noordin

    Published 2019
    “…Many researches have been done in the detection or classification of wrinkle, but it still needs some improvement in the algorithms, either in feature extraction part or classification. …”
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  14. 14
    Poverty risk prediction based on socioeconomic factors using machine learning approach

    Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

    Published 2025
    “…The findings indicated that the Logistic Regression outperformed the other algorithm with 99.06% using cross-validation and 98.42% using the splitting method, and with the best value of precision, recall, and F1-score. …”
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  15. 15
    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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  16. 16
    Predicting the classification of heart failure patients using optimized machine learning algorithms

    Predicting the classification of heart failure patients using optimized machine learning algorithms by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md Maruf, Bhuiyan, Touhid

    Published 2025
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  17. 17
    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization

    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

    Published 2021
    “…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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  18. 18
    Prediction of payment method in convenience stores using machine learning

    Prediction of payment method in convenience stores using machine learning by Pratondo, Agus, Novianty, Astri, Pudjoatmodjo, Bambang

    Published 2023
    “…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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  19. 19
    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data

    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2013
    “…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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  20. 20
    Malware Classification and Detection using Variations of Machine Learning Algorithm Models

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

    Published 2025
    “…Types of attacks can be Ping of Death, flooding, remote-controlled attacks, UDP flooding, and Smurf Attacks. Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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