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  • Open Access

    ARTICLE

    Horizontal Voting Ensemble Based Predictive Modeling System for Colon Cancer

    Ushaa Eswaran1,*, S. Anand2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1917-1928, 2023, DOI:10.32604/csse.2023.032523

    Abstract Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models… More >

  • Open Access

    ARTICLE

    Automatic Leukaemia Segmentation Approach for Blood Cancer Classification Using Microscopic Images

    Anuj Sharma1, Deepak Prashar2, Arfat Ahmad Khan3, Faizan Ahmed Khan4, Settawit Poochaya3,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3629-3648, 2022, DOI:10.32604/cmc.2022.030879

    Abstract Leukaemia is a type of blood cancer that is caused by undeveloped White Blood Cells (WBC), and it is also called a blast blood cell. In the marrow of human bones, leukaemia is developed and is responsible for blood cell generation with leukocytes and WBC, and if any cell gets blasted, then it may become a cause of death. Therefore, the diagnosis of leukaemia in its early stages helps greatly in the treatment along with saving human lives. Subsequently, in terms of detection, image segmentation techniques play a vital role, and they turn out to be the important image processing… More >

  • Open Access

    ARTICLE

    Fractal Dimension Analysis Based Aging State Assessment of Insulating Paper with Surface Microscopic Images

    Shuaibing Li1,*, Jiaqi Cui2, Yongqiang Kang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1083-1099, 2022, DOI:10.32604/cmes.2022.019671

    Abstract The insulating paper of the transformer is affected by many factors during the operation, meanwhile, the surface texture of the paper is easy to change. To explore the relationship between the aging state and surface texture change of insulating paper, firstly, the thermal aging experiment of insulating paper is carried out, and the insulating paper samples with different aging times are obtained. After then, the images of the aged insulating paper samples are collected and pre-processed. The pre-processing effect is verified by constructing and calculating the gray surface of the sample. Secondly, the texture features of the insulating paper image… More >

  • Open Access

    ARTICLE

    Drug Response Prediction of Liver Cancer Cell Line Using Deep Learning

    Mehdi Hassan1,*, Safdar Ali2, Muhammad Sanaullah3, Khuram Shahzad4, Sadaf Mushtaq5,6, Rashda Abbasi6, Zulqurnain Ali4, Hani Alquhayz7

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2743-2760, 2022, DOI:10.32604/cmc.2022.020055

    Abstract Cancer is the second deadliest human disease worldwide with high mortality rate. Rehabilitation and treatment of this disease requires precise and automatic assessment of effective drug response and control system. Prediction of treated and untreated cancerous cell line is one of the most challenging problems for precise and targeted drug delivery and response. A novel approach is proposed for prediction of drug treated and untreated cancer cell line automatically by employing modified Deep neural networks. Human hepatocellular carcinoma (HepG2) cells are exposed to anticancer drug functionalized CFO@BTO nanoparticles developed by our lab. Prediction models are developed by modifying ResNet101 and… More >

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