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  1. 1
    Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter

    Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter by Tengku Azis, Tengku Mohd Syamim

    Published 2015
    “…In this research, a Gabor-based emphysema classification algorithm is proposed. …”
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  2. 2
    Effective gene selection techniques for classification of gene expression data

    Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

    Published 2005
    “…The selected subset of genes is then be used to train the classifiers for constructing rules for future tissue classification problem. …”
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  3. 3
    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim

    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim by Ibrahim, Shafaf

    Published 2015
    “…It is designed to incorporate with the CAPSOCA algorithm which intended to strengthen the classification outcomes. …”
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  4. 4
    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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  5. 5
    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm

    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

    Published 2015
    “…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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  6. 6
    Development of sorting system for oil palm in vitro shoots using machine vision approach

    Development of sorting system for oil palm in vitro shoots using machine vision approach by Al-Ruhaimi, Hamdan Yahya Ahmed

    Published 2014
    “…Based on SOTA and classification task decision, a sorting algorithm that can acquire, recognize, and eject a shoot has been improved and tested in an offline mode. …”
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  7. 7
    Texture Classification of lung computed tomography (CT) using local binary patterns (LBP)

    Texture Classification of lung computed tomography (CT) using local binary patterns (LBP) by MOHD YUSRI, MOHAMAD AFIF SYAUQI

    Published 2015
    “…In this work, we proposed an LBP-based lung classification algorithm. The local binary pattern (LBP) is one of the feature extraction technique that can be used in classify the image. …”
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  8. 8
    Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique

    Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique by Jais, Fatin Nabihah, Che Azemin, Mohd Zulfaezal, Hilmi, Mohd Radzi, Mohd Tamrin, Mohd Izzuddin, Mohd. Kamal, Khairidzan

    Published 2021
    “…Conclusion. Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.…”
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  9. 9
    Breast cancer histological images nuclei segmentation and optimized classification with deep learning

    Breast cancer histological images nuclei segmentation and optimized classification with deep learning by Abbasi, Muhammad Inam, Khan, Fawad Salam, Khurram, Muhammad, Mohd, Mohd Norzali, Khan, Muhammad Danial

    Published 2022
    “…A breast cancer multi-classification technique based on a suggested deep learning algorithm was examined to achieve the accuracy of 99.2% using a huge database of ICIAR 2018, demonstrating the method’s efficacy in offering an important weapon for breast cancer multi-classification in a medical setting. …”
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  10. 10
    Breast cancer classification using mammography image and K-Nearest Neighbour / Najihah Ahmad Latif

    Breast cancer classification using mammography image and K-Nearest Neighbour / Najihah Ahmad Latif by Ahmad Latif, Najihah

    Published 2020
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  11. 11
    Automated classification radiograph of Periodontal bone loss using deep learning

    Automated classification radiograph of Periodontal bone loss using deep learning by Al Husaini, Mohammed Abdulla Salim, Habaebi, Mohamed Hadi, Yadav, Seema

    Published 2025
    “…This study highlights the potential of deep learning-based OPG classification systems to assist dental professionals in faster and more accurate detection of periodontal diseases.…”
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  12. 12
    Development of predictive modeling and deep learning classification of taxi trip tolls

    Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

    Published 2022
    “…In this work, let’s use the classification learner to create classification models, compare their performance, and export the findings for additional study. …”
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  13. 13
    EMG signal classification for human computer interaction: a review

    EMG signal classification for human computer interaction: a review by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2009
    “…This review paper is to discuss the various methodologies and algorithms used for EMG signal classification for the purpose of interpreting the EMG signal into computer command.…”
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  14. 14
    A review of classification techniques for electromyography signals

    A review of classification techniques for electromyography signals by Mohd Saad, Norhashimah, Omar, Siti Nashayu, Abdullah, Abdul Rahim, Shair, Ezreen Farina, H.Rashid

    Published 2023
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  15. 15
    Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review

    Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Fatimah, Dzaharudin, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

    Published 2021
    “…Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. …”
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  16. 16
    DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS

    DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS by Al-Shoukry S., Jawad B.J.M., Musa Z., Sabry A.H.

    Published 2023
    “…In this work, let�s use the classification learner to create classification models, compare their performance, and export the findings for additional study. …”
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  17. 17
    Automated Segmentation And Classification Technique For Brain Stroke

    Automated Segmentation And Classification Technique For Brain Stroke by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim, Mohd Noor, Niza Suzaini, Mohd Ali, Nursabillilah

    Published 2019
    “…This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). …”
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  18. 18
    Evaluation of heuristic-based MicroRNA marker selection techniques for classification of cancer

    Evaluation of heuristic-based MicroRNA marker selection techniques for classification of cancer by Razak, Eliza, Yusof, Faridah, Ahmad Raus, Raha

    Published 2016
    “…In this paper, we employed three marker selection algorithms to select relevant miRNAs that are directly responsible for cancer classification. …”
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  19. 19
    Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images

    Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images by Gandhamal, A., Talbar, S., Gajre, S., Hani, A.F.M., Kumar, D.

    Published 2017
    “…The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. © 2017 Elsevier Ltd…”
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  20. 20
    Ganoderma boninense disease detection by Near-Infrared Spectroscopy Classification: a review

    Ganoderma boninense disease detection by Near-Infrared Spectroscopy Classification: a review by Mohd Hilmi Tan, Mas Ira Syafila, Jamlos, Mohd Faizal, Omar, Ahmad Fairuz, Dzaharudin, Fatimah, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

    Published 2021
    “…Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. …”
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