Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (174)
  • Open Access

    ARTICLE

    Mammogram Learning System for Breast Cancer Diagnosis Using Deep Learning SVM

    G. Jayandhi1,*, J.S. Leena Jasmine2, S. Mary Joans2

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 491-503, 2022, DOI:10.32604/csse.2022.016376

    Abstract The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces system complexity. The softmax layer… More >

  • Open Access

    ARTICLE

    An Efficient Breast Cancer Detection Framework for Medical Diagnosis Applications

    Naglaa F. Soliman1,2, Naglaa S. Ali2, Mahmoud I. Aly2,3, Abeer D. Algarni1,*, Walid El-Shafai4, Fathi E. Abd El-Samie1,4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1315-1334, 2022, DOI:10.32604/cmc.2022.017001

    Abstract Breast cancer is the most common type of cancer, and it is the reason for cancer death toll in women in recent years. Early diagnosis is essential to handle breast cancer patients for treatment at the right time. Screening with mammography is the preferred examination for breast cancer, as it is available worldwide and inexpensive. Computer-Aided Detection (CAD) systems are used to analyze medical images to detect breast cancer, early. The death rate of cancer patients has decreased by detecting tumors early and having appropriate treatment after operations. Processing of mammogram images has four main steps: pre-processing, segmentation of the… More >

  • Open Access

    ARTICLE

    Breast Cancer Classification Using Deep Convolution Neural Network with Transfer Learning

    Hanan A. Hosni Mahmoud*, Amal H. Alharbi, Doaa S. Khafga

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 803-814, 2021, DOI:10.32604/iasc.2021.018607

    Abstract In this paper, we aim to apply deep learning convolution neural network (Deep-CNN) technology to classify breast masses in mammograms. We develop a Deep-CNN combined with multi-feature extraction and transfer learning to detect breast cancer. The Deep-CNN is utilized to extract features from mammograms. A support vector machine (SVM) is then trained on the Deep-CNN features to classify normal, benign, and cancer cases. The scoring features from the Deep-CNN are coupled with texture features and used as inputs to the final classifier. Two texture features are included: texture features of spatial dependency and gradient-based histograms. Both are employed to locate… More >

  • Open Access

    ARTICLE

    Tannin Nanoparticles (NP99) Enhances the Anticancer Effect of Tamoxifen on ER+ Breast Cancer Cells

    Faizah A. AlMalki1, Aziza M. Hassan2,*, Zeinab M. Klaab1, Soliman Abdulla3, Antonio Pizzi4

    Journal of Renewable Materials, Vol.9, No.12, pp. 2077-2092, 2021, DOI:10.32604/jrm.2021.016173

    Abstract Recently, natural substances in the form of nanoparticles are increasingly being used in different field, particularly in medicines to enhance their beneficial effects in treatment and prevention. Cancer cells of the breast (MCF-7) have been chosen to be examined and treated in vitro with conventional drug Tamoxifen (Tam) and tannin nanoparticles extract (NP99) individually or in combination. MTT reagent has been applied to assess the cell viability and propagation percentage, DNA fragmentation and mRNA relative expression of apoptotic genes to study the cell death pathway. The results showed that Tam and tannin NP99 triggered cytotoxic activity towards the MCF-7 cell.… More >

  • Open Access

    ARTICLE

    Prolonged Survival in Patients with Human Epidermal Growth Factor Receptor-2-Overexpressed Metastatic Breast Cancer after Targeted Therapy is Dominantly Contributed by Luminal-Human Epidermal Growth Factor Receptor-2 Population

    Keiichi Kontani1,*, Kana Kuraishi1, Shin-ichiro Hashimoto1, Shoko Norimura2, Nozomi Hashimoto1, Masahiro Ohtani3, Naomi Fujiwara-Honjo4, Manabu Date5, Koji Teramoto6, Hiroyasu Yokomise1

    Oncologie, Vol.23, No.2, pp. 229-239, 2021, DOI:10.32604/Oncologie.2021.016277

    Abstract The prognosis of patients with human epidermal growth factor receptor-2 (HER2)-overexpressed metastatic breast cancer (MBC) has improved drastically following the development of anti-HER2 therapies. We question what factors are involved in the improved outcome by the treatment. One hundred and two MBC patients who received chemotherapy were classified into groups according to breast cancer subtype: luminal/HER2-negative (n = 50), HER2 (n = 26), and triple-negative subtypes (n = 26). Clinicopathologic features and clinical outcomes of the groups were compared. Disease-free intervals in the triple-negative group were significantly shorter than those in the other two groups. Age, tumor grade, the number… More >

  • Open Access

    ARTICLE

    Breast Lesions Detection and Classification via YOLO-Based Fusion Models

    Asma Baccouche1,*, Begonya Garcia-Zapirain2, Cristian Castillo Olea2, Adel S. Elmaghraby1

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1407-1425, 2021, DOI:10.32604/cmc.2021.018461

    Abstract With recent breakthroughs in artificial intelligence, the use of deep learning models achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous applications provided efficient solutions to assist radiologists for medical imaging analysis. For instance, automatic lesion detection and classification in mammograms is still considered a crucial task that requires more accurate diagnosis and precise analysis of abnormal lesions. In this paper, we propose an end-to-end system, which is based on You-Only-Look-Once (YOLO) model, to simultaneously localize and classify suspicious breast lesions from entire mammograms. The proposed system first preprocesses the raw images, then recognizes abnormal regions as… More >

  • Open Access

    ARTICLE

    Machine Learning Techniques Applied to Electronic Healthcare Records to Predict Cancer Patient Survivability

    Ornela Bardhi1,2,*, Begonya Garcia Zapirain1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1595-1613, 2021, DOI:10.32604/cmc.2021.015326

    Abstract Breast cancer (BCa) and prostate cancer (PCa) are the two most common types of cancer. Various factors play a role in these cancers, and discovering the most important ones might help patients live longer, better lives. This study aims to determine the variables that most affect patient survivability, and how the use of different machine learning algorithms can assist in such predictions. The AURIA database was used, which contains electronic healthcare records (EHRs) of 20,006 individual patients diagnosed with either breast or prostate cancer in a particular region in Finland. In total, there were 178 features for BCa and 143… More >

  • Open Access

    ARTICLE

    Accès au premier traitement : apport d’un centre de prise en charge rapide
    Access to First Treatment: Contribution of a Quick Care Centre

    E. du Rouchet, C. Dendoncker

    Oncologie, Vol.21, No.2, pp. 125-134, 2019, DOI:10.3166/onco-2019-0042

    Abstract For a patient suffering from breast cancer, access to the initial treatment includes several steps like confirmation of an anatomopathological diagnosis, proposition and establishment of an individualized treatment plan, pretreatment assessments, and access to the technical platform. The accumulated duration of these intervals plays a role in the prognosis in the early stages of the disease. In addition, it is important to manage all the uncertainties, both diagnostic and prognostic, which will inevitably upset the patient’s psychological balance. Supported by literature, recommendations and more than 20 years of experience in a multidisciplinary centre, the authors propose the organization of an… More >

  • Open Access

    ARTICLE

    Place des CTC et de l’ADN circulant dans la prise en charge du cancer du sein
    CTC and cDNA in Breast Cancer Management

    V. Allouchery, L. Augusto, F. Clatot

    Oncologie, Vol.21, No.1, pp. 40-48, 2019, DOI:10.3166/onco-2019-0035

    Abstract It has been known for a long time that circulating tumor cells (CTC) as well as circulating tumor DNA (ctDNA) can be detected. However, only recent technical advances allowed evaluating the interest of CTC and ctDNA in breast cancer. In both early and metastatic breast cancers, CTC detection is a recognized factor for poor outcome. Nevertheless, CTC detection does not impact cancer management yet. The use of ctDNA in daily practice will require validation by prospective data. But ctDNA seems particularly promising both for residual disease evaluation and identification of tumor clones harbouring mutations (PI3KC, ESR1) and may predict efficacy… More >

  • Open Access

    ARTICLE

    Cancers du sein triple-négatifs : données actuelles et perspectives d’avenir
    Triple-Negative Breast Cancer: Current Data and Future Prospects

    A. de Nonneville, A. Gonçalves

    Oncologie, Vol.21, No.1, pp. 33-39, 2019, DOI:10.3166/onco-2019-0039

    Abstract Triple-negative breast cancer (TNBC), defined by the lack of expression of hormone receptors and HER2 (Human Epidermal growth factor Receptor-2), accounts for 15–20% of breast cancers. However, this definition, which is essentially negative, masks the large biological heterogeneity of this subtype. While chemotherapy is the main established systemic treatment in both early and advanced stages of the disease, the progressive understanding of the molecular components involved in the pathogenesis of TNBC allows innovative therapeutic perspectives. The objective of this review is to describe these potential targets and to explore current and future treatments that will help fighting this cancer with… More >

Displaying 141-150 on page 15 of 174. Per Page