Search Results - (( effective classification cell algorithm ) OR ( java implication based algorithm ))

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  1. 1

    Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

    Published 2021
    “…In order to classify the breast cancer cells, an accurate and effective classification model is needed. …”
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    Student Project
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    Red blood cells classification with sharpening segmentation and mask R-CNN by Arianti, Nunik Destria, Muda, Azah Kamilah, Ahmad, Norashikin

    Published 2023
    “…This paper proposes classification using sharpening segmentation combined with the algorithm mask R-CNN to increase the accuracy of calculating the number of RBCs. …”
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    Conference or Workshop Item
  4. 4

    Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

    Published 2019
    “…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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    Final Year Project
  5. 5

    Blood cell image segmentation using unsupervised clustering techniques by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina

    Published 2009
    “…The aim of our research is to develop an effective algorithm for segmentation of the blood cell images. …”
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    Conference or Workshop Item
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    Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images by Baharom, Mohamad Shahrul Affendi

    Published 2019
    “…But, some structure of unnecessary cell accidently be removed such as small cell or damaged cell. …”
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    Thesis
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    The Significant Effect of Feature Selection Methods in Spam Risk Assessment Using Dendritic Cell Algorithm by Zainal, K, Jali, MZ

    Published 2024
    “…This feature selection method then further fed in conjunction with the Dendritic Cell Algorithm (DCA) as the classifier to measure the risk concentration of a spam message. …”
    Proceedings Paper
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    Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab by Wahhab, Hayan Tareq Abdul

    Published 2015
    “…The seeded region growing was used to further segment the blast cell into nucleus and cytoplasm, respectively. This combination resulted in a new algorithm we named CBCSA. …”
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    Thesis
  11. 11

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…Experimental results on real-world machine learning benchmark data sets have demonstrated the effectiveness of the proposed algorithms. …”
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    Thesis
  12. 12

    An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing by Hajyyev, Abdyrahym

    Published 2014
    “…The algorithm tested on the publicly available Mivia Hep-2 Cell image dataset. …”
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    Final Year Project
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    Klasifikasi Sel-Sel Kanser Payudara Menggunakan Rangkaian Neural Peta-Peta Penubuhan-Diri (Som) by Mohd Salleh, Nuryanti

    Published 2006
    “…Therefore, the purpose of this project is to investigate the possibility of neural network methods in classifying breast cancer cells. In this project, breast cancer cells classification was achieved based on Self-Organizing Maps Kohonen 2-Dimension neural network. …”
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    Monograph
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    Prioritizing CD4 count monitoring in response to ART in resource-constrained settings: a retrospective application of prediction-based classification by Azzoni, Livio, Foulkes, Andrea S., Liu, Yan, Johnson, Margaret, Smith, Collette, Kamarulzaman, Adeeba, Montaner, Julio, Mounzer, Karam, Saag, Michael, Cahn, Pedro, Cesar, Carina, Krolewiecki, Alejandro, Sanne, Ian, Montaner, Luis J.

    Published 2012
    “…Methods and Findings: Using a prospective cohort of HIV-infected patients (n = 1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4+ T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4+ T cell count of 200 or 350 cells/ml). …”
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    Article
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    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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    Article
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    Development of rheumatoid arthritis classification from electronic image sensor using ensemble method by Sharon, H., Elamvazuthi, I., Lu, C.-K., Parasuraman, S., Natarajan, E.

    Published 2020
    “…The RA dataset was gathered from the analysis of white blood cell classification using features extracted from the image of lymphocytes acquired from a digital microscope with an electronic image sensor. …”
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    Article
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    Early Diagnosis of Non-small-cell lung Carcinoma from Gene Expression Using t-Distributed Stochastic Neighbor Embedding by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…One of the most promising techniques for early detection of cancerous cells depends on machine learning based on molecular cancer classification using gene expression profiling data. …”
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    Proceeding Paper