Breast cancer detection using machine learning algorithms. 1–4 (2014) Jan 31, 2022 · A prediction model is proposed, which is specifically designed for prediction of Breast Cancer using Machine learning algorithms Decision tree classifier, Naïve Bayes, SVM and KNearest Neighbour algorithms. 5th international conference on electronic devices, systems and applications (ICEDSA) (pp. This study presents a detailed comparison of seventeen machine learning algorithms applied to the Wisconsin Diagnostic Breast Cancer (WDBC) and Breast Cancer Coimbra (BCCD) datasets. Abstract Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide, making early and accurate diagnosis essential for improving survival rates and treatment outcomes. 1–4). This study explores the application of machine learning algorithms in detecting breast cancer, aiming to improve early diagnosis and patient outcomes. Jan 1, 2025 · In bioinformatics, the integration of machine learning has revolutionized disease diagnosis. Amir , BREAST CANCER DETECTION USING DEEP LEARNING , Volume 7 , Issue 4, april 2022, EPRA International Journal of Research & Development (IJRD) , The study successfully leverages the data from the METABRIC dataset, demonstrating the effectiveness of different machine-learning models in predicting these key cancer-related factors. . Early detection dramatically improves survival rates. 9% precision, 100% Leveraging Machine Learning Algorithms for Early Detection of Breast Cancer: A Comparative Study Using Diagnostic Features Machine learning has shown considerable promise in supporting clinical decision-making by enabling timely and reliable disease detection. Patient compliance, cost and resource constraints, and genetic and molecular factors also contribute to the challenges faced in breast cancer screening. Oct 17, 2025 · This study optimizes breast cancer prediction using various machine learning algorithms, including K-Nearest Neighbors, Support Vector Machine, Decision Trees, and ensemble methods such as Bagging and Boosting, to highlight the promise of machine learning in early breast cancer detection. Multiple machine-learning algorithms were utilized to determine whether the tumor was benign or Access to breast cancer screening can be limited by socioeconomic factors, geographic location, and healthcare disparities, resulting in missed opportunities for early detection. Aug 29, 2025 · Machine learning provides an excellent tool in the continuous battle for breast cancer, and early detection continues to be one of its most successful methods to tackle this fatal disease. 3% accuracy, 98. Abstract: Data analytics play vital roles in diagnosis and treatment in the health care sector. The model analyzes properties like: Radius, Texture, Perimeter, Area of the tumor A comparative study of breast cancer detection based on SVM and MLP BPN classifier. To address limitations associated with conventional diagnostic methods, Machine Learning (ML) techniques have been increasingly adopted to enhance classification accuracy and reduce Breast-Cancer-Detection-Using-Machine-Learning Developed a Python-based system to predict whether a tumor is malignant or benign using machine learning algorithms. To enable practitioner decisionmaking, huge volumes of data should be processed with machine Besides, the results show that the proposed models are able to outperform recent classical machine learning algorithms. Comparative study of machine learning algorithms for breast cancer detection and diagnosis. This research contributes to the field of personalized medicine by providing objective findings on breast cancer detection and therapy. Machine learning algorithms remove human limitations, offering more accuracy in diagnosing diseases like cancer. How to Cite: Shrutika Netke, Archana Potraj, Sayyed Mohd. Breast Cancer Detection Using Machine Learning Models Today, I completed a machine learning project focused on breast cancer prediction using multiple classification algorithms to identify the Breast cancer is the most common cancer among women worldwide. Breast cancer, the second most diagnosed cancer in women, often relies on mammography, which is only 70 % accurate, leading to potential misdiagnosis. Jul 24, 2025 · This study used machine learning approaches and explainable AI to predict breast cancer detection. Biopsies, though more reliable, are Mar 24, 2023 · When we compare the developed machine learning algorithms; K-Nearest Neighbor algorithm showed higher performance than other machine learning algorithms with 99. This project leverages machine learning to assist in identifying whether a tumor is benign or malignant based on 30 digitized features computed from a fine needle aspirate (FNA) of a breast mass. In: 2014 First International Conference on Automation, Control, Energy and Systems (ACES), Hooghy, pp. bvpoz rsvk nqpk xgyhwy yvuzh mbf obrz knn umd niuimss