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  • Open Access

    ARTICLE

    Tumor-Associated Macrophages Facilitate the Proliferation and Migration of Cervical Cancer Cells

    Yi Zheng1, Youyou Wang2, Chen Zou1, Bicheng Hu2, Min Zhao2, Xinxing Wu2,*

    Oncologie, Vol.24, No.1, pp. 147-161, 2022, DOI:10.32604/oncologie.2022.019236 - 31 March 2022

    Abstract Tumor-associated macrophages (TAMs) are important components in tumor microenvironment. This study intended to explore the influence of TAMs on cervical cancer cells proliferation and migration. The expression levels of TAMs markers, CD68 and CD163, in tissues were examined by immunohistochemistry and increased with the progression of cervical lesions (p < 0.05). TAMs with M2-like phenotype (PMA(Polymethacrylate) induced THP-1 cells) were noticed to promote the proliferation of cervical cancer cells and improve the migration ability of tumor cells. These enhancements were attributed to secreting soluble components and the physical contact between macrophages and tumor cells. The tumor More >

  • Open Access

    ARTICLE

    Segmentation of Cervical Cancer by OLHT Based DT-CWT Techniques

    P. R. Sheebha Rani1,*, R. Jemila Rose2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1579-1592, 2022, DOI:10.32604/iasc.2022.023587 - 24 March 2022

    Abstract Every year, cervical cancer (CC) is the leading cause of death in women around the world. If detected early enough, this cancer can be treated, and patients will receive adequate care. This study introduces a novel ultrasound-based method for detecting CC. The Oriented Local Histogram Technique (OLHT) is used to improve the image corners in the cervical image (CI), and the Dual-Tree Complex Wavelet Transform (DT-CWT) is used to build a multi-resolution image (CI). Wavelet, and Local Binary Pattern are among the elements retrieved from this improved multi-resolution CI (LBP). The retrieved appearance is trained More >

  • Open Access

    ARTICLE

    Optimal Deep Learning Based Inception Model for Cervical Cancer Diagnosis

    Tamer AbuKhalil1, Bassam A. Y. Alqaralleh2,*, Ahmad H. Al-Omari3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 57-71, 2022, DOI:10.32604/cmc.2022.024367 - 24 February 2022

    Abstract Prevention of cervical cancer becomes essential and is carried out by the use of Pap smear images. Pap smear test analysis is laborious and tiresome work performed visually using a cytopathologist. Therefore, automated cervical cancer diagnosis using automated methods are necessary. This paper designs an optimal deep learning based Inception model for cervical cancer diagnosis (ODLIM-CCD) using pap smear images. The proposed ODLIM-CCD technique incorporates median filtering (MF) based pre-processing to discard the noise and Otsu model based segmentation process. Besides, deep convolutional neural network (DCNN) based Inception with Residual Network (ResNet) v2 model is More >

  • Open Access

    ARTICLE

    Intelligent Classification Model for Biomedical Pap Smear Images on IoT Environment

    CSS Anupama1, T. J. Benedict Jose2, Heba F. Eid3, Nojood O Aljehane4, Fahd N. Al-Wesabi5,*, Marwa Obayya6, Anwer Mustafa Hilal7

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3969-3983, 2022, DOI:10.32604/cmc.2022.022701 - 07 December 2021

    Abstract Biomedical images are used for capturing the images for diagnosis process and to examine the present condition of organs or tissues. Biomedical image processing concepts are identical to biomedical signal processing, which includes the investigation, improvement, and exhibition of images gathered using x-ray, ultrasound, MRI, etc. At the same time, cervical cancer becomes a major reason for increased women's mortality rate. But cervical cancer is an identified at an earlier stage using regular pap smear images. In this aspect, this paper devises a new biomedical pap smear image classification using cascaded deep forest (BPSIC-CDF) model… More >

  • Open Access

    REVIEW

    Cervical cancer situation in Malaysia: A systematic literature review

    WAN AZANI MUSTAFA1,2,*, AFIQAH HALIM2, MOHD WAFI NASRUDIN2, KHAIRUL SHAKIR AB RAHMAN3

    BIOCELL, Vol.46, No.2, pp. 367-381, 2022, DOI:10.32604/biocell.2022.016814 - 20 October 2021

    Abstract Cervix cancer is one of Malaysia’s most significant cancers for women (around 12.9%, with an age-standardised incidence rate of 19.7 per 100,000). It was higher than other Asian, West, and even worldwide nations. The National Strategic Plan for Cancer Control Program 2016–2020 (Health Ministry) was presented to minimize cancer and mortality. The high incidence of cervical cancer in Malaysia is mainly due to women’s insufficient knowledge about its prevention and importance. Compared with traditional literature reviews, the systemic analysis provides many advantages. A clearer review process, a more prominent field of study, and essential priorities More >

  • Open Access

    ARTICLE

    Optimal Deep Convolution Neural Network for Cervical Cancer Diagnosis Model

    Mohamed Ibrahim Waly1, Mohamed Yacin Sikkandar1, Mohamed Abdelkader Aboamer1, Seifedine Kadry2, Orawit Thinnukool3,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3295-3309, 2022, DOI:10.32604/cmc.2022.020713 - 27 September 2021

    Abstract Biomedical imaging is an effective way of examining the internal organ of the human body and its diseases. An important kind of biomedical image is Pap smear image that is widely employed for cervical cancer diagnosis. Cervical cancer is a vital reason for increased women’s mortality rate. Proper screening of pap smear images is essential to assist the earlier identification and diagnostic process of cervical cancer. Computer-aided systems for cancerous cell detection need to be developed using deep learning (DL) approaches. This study introduces an intelligent deep convolutional neural network for cervical cancer detection and… More >

  • Open Access

    ARTICLE

    Design of Computer Methods for the Solution of Cervical Cancer Epidemic Model

    Ali Raza1, Muhammad Rafiq2, Dalal Alrowaili3, Nauman Ahmed4, Ilyas Khan5,*, Kottakkaran Sooppy Nisar6, Muhammad Mohsin7

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1649-1666, 2022, DOI:10.32604/cmc.2022.019148 - 07 September 2021

    Abstract Nonlinear modelling has a significant role in different disciplines of sciences such as behavioral, social, physical and biological sciences. The structural properties are also needed for such types of disciplines, as dynamical consistency, positivity and boundedness are the major requirements of the models in these fields. One more thing, this type of nonlinear model has no explicit solutions. For the sake of comparison its computation will be done by using different computational techniques. Regrettably, the aforementioned structural properties have not been restored in the existing computational techniques in literature. Therefore, the construction of structural preserving… More >

  • Open Access

    REVIEW

    Improvement method for cervical cancer detection: A comparative analysis

    NUR AIN ALIAS1, WAN AZANI MUSTAFA1,2,*, MOHD AMINUDIN JAMLOS3, AHMED ALKHAYYAT4, KHAIRUL SHAKIR AB RAHMAN5, RAMI Q. MALIK6

    Oncology Research, Vol.29, No.5, pp. 365-376, 2021, DOI:10.32604/or.2022.025897 - 10 October 2022

    Abstract Cervical cancer is a prevalent and deadly cancer that affects women all over the world. It affects about 0.5 million women anually and results in over 0.3 million fatalities. Diagnosis of this cancer was previously done manually, which could result in false positives or negatives. The researchers are still contemplating how to detect cervical cancer automatically and how to evaluate Pap smear images. Hence, this paper has reviewed several detection methods from the previous researches that has been done before. This paper reviews pre-processing, detection method framework for nucleus detection, and analysis performance of the… More >

  • Open Access

    ARTICLE

    Suppression of human papillomavirus type 16 E5 oncoprotein: A promising step in fostering the treatment of cervical cancer

    NIMA HEMMAT1, MOHAMMAD AMIN DOUSTVANDI1, ZAHRA ASADZADEH1, AHAD MOKHTARZADEH1, BEHZAD BARADARAN1,4,*, HOSSEIN BANNAZADEH BAGHI1,2,3,*

    Oncology Research, Vol.29, No.2, pp. 141-148, 2021, DOI:10.32604/or.2022.023346 - 13 July 2022

    Abstract Cervical cancer is a growing global disease in developing countries. Persistent infection with human papillomaviruses (HPV) is an essential causative agent in this type of cancer. Several studies demonstrate HPV E5 oncoprotein can impress the normal life cycle of HPV-infected cells by targeting some pivotal cellular signaling pathways, such as the epidermal growth factor receptor (EGFR) signaling pathway. In this study, we used E5-siRNA to knockdown that essential oncogene and considered the effect of E5 silencing on proliferation, apoptosis, cell cycle, apoptosis-related gene expression, and the initiator of the EGFR signaling pathway in cervical cancer More >

  • Open Access

    ARTICLE

    Awareness of Human Papilloma Virus and Its Association with Cervical Cancer among Female University Students: A Study from United Arab Emirates

    Madhumitha Kedhari Sundaram1, Abdulmajeed G. Almutary2, Shafiul Haque3, Faheem SM1, Arif Hussain1,*

    Oncologie, Vol.23, No.2, pp. 269-277, 2021, DOI:10.32604/Oncologie.2021.016002 - 22 June 2021

    Abstract Cervical cancer is the neoplasm of the uterine cervix in women, which is highly preventable. With the advent of vaccination against HPV infection, a gradual decline in the incidence of cervical cancer cases has been observed in developing countries. The developing nations bear the brunt of cervical cancer incidence due to low acceptance of vaccination. This survey-based study was designed to assess the awareness and opinions of female university students regarding human papilloma virus, vaccination and cervical cancer. A survey questionnaire was distributed among female expatriate students (18 to 26 years of age) of a… More >

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