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7 articles for “Enhanced Cancer Classification”
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Research ArticleOpen accessIn the keywordsOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 accessesView PDFCite
Review ArticleOpen accessIn the abstractChallenges of Breast Cancer Detection Based on Histopathology ImagesAlaa Mohamed Youssef, Aliaa Abdel-Haleim Abdel-Razik Youssif, Wessam El BehaidyArtificial Intelligence (AI) is rapidly evolving every day to become increasingly potent and dependable. AI systems are becoming more sophisticated and are being utilized across various domains with the goal of enhancing human existence. Within the healthcare system, artificial intelligence finds application in handling and documenting large volumes of medical data, conducting analyses of healthcare systems, advancing pharmaceutical development, and … …Journal of Computer Science, Vol. 20, Issue 7 · 17 Apr 2024 · 4,942 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassify Breast Cancer Patients using Hybrid Data-Mining TechniquesFaris E. Mohammed, Nadia Smaoui Zghal, Dalinda Ben Aissa, Mostafa Mahmoud El-GayarAccording to the World Health Organization (WHO), breast cancer is a disease that leads to death, especially for women who have neglected or ignored the risk factors. Doctors can classify patients according to clinical information, famous disease symptoms, or similar cases. But, some cases are difficult to detect early or diagnose accurately. Therefore, the most important challenge faced by researchers … …Journal of Computer Science, Vol. 18, Issue 4 · 12 May 2022 · 6,526 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Support Vector Machine based on Metaheuristic Search for Multiclass ProblemsAbdullah Saeed Ghareb, Mohammed Hamid Afif, Abdel-Rahman Hedar et al.Machine learning is an important field of artificial intelligent researches and it highly growing for real intelligent applications systems that relate brain computer interface to human brain activities. Support Vector Machine (SVM) is a popular machine learning approach, which can be used for pattern recognition, prediction and classification with many diverse applications. However, the SVM has many parameters, which have … …Journal of Computer Science, Vol. 16, Issue 7 · 9 Jul 2020 · 6,906 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordHematologic Cancer Cell Detection and Classification Using Optimized VGG-19 with Stratified K-fold Cross-ValidationHema Patel, Himal Shah, Gayatri Patel, Atul PatelThe most prevalent pediatric blood malignancy is acute lymphoblastic leukemia (ALL). ALL is a lethal disease in which patients have a lower survival rate. Its prompt detection and precise categorization are essential for successful treatment. Manual microscopic diagnosis is laborious, prone to mistakes, and heavily reliant on specialized knowledge. With stratified 7-fold cross-validation, which assures an equal ratio of normal … …Journal of Computer Science, Vol. 21, Issue 11 · 24 Dec 2025 · 1,812 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAdaptive Data Transformation for Enhanced Clustering Performance in Diagnostic SystemsMohammed Subhi Al-BatahThis paper presents an enhanced approach to the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm, aimed at improving clustering accuracy in medical data, specifically for breast cancer diagnosis. The proposed method introduces a modified data transformation technique to optimize the original BIRCH algorithm. This transformation refines the clustering process, resulting in significant improvements in diagnostic accuracy. The modified … …Journal of Computer Science, Vol. 21, Issue 9 · 17 Oct 2025 · 2,287 accessesView PDFCite