Development of an Algorithm and Software Tool for Early Diagnosis of Breast Cancer Based on Intelligent Analysis
Keywords:
Breast cancer detection, Artificial Intelligence, Machine Learning, Deep Learning, Medical Imaging, Convolutional Neural Networks, Support Vector Machines, Random Forest, K-Nearest Neighbors, Artificial Neural Networks, Recurrent Neural Networks, Feature Extraction, Early Diagnosis.Abstract
Breast cancer is one of the most common and life-threatening diseases among women worldwide. Early diagnosis plays a crucial role in increasing survival rates and improving treatment effectiveness. This article presents an approach that leverages artificial intelligence (AI) and machine learning (ML) techniques to develop an algorithm and software tool for the early detection of breast cancer. The proposed system integrates medical imaging, deep learning models, and data-driven analytics to enhance diagnostic accuracy.
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