Approach to Predict Early Stage of Breast Cancer using Machine Learning
R. Raja Sekar, Midigesi Rakesh Kumar, Mandala Vishnu Vardhan, K Venu Gopal, C Jayakkan Allan Tilak · 2023
In the world, breast cancer is regarded as one of the main factors that cause death for females between the ages of 20 and 59. Early detection and treatment can enable patients to receive appropriate care, hence lowering the rate of breast cancer morbidity. In line with research, most experienced doctors can correctly identify cancer with 79% accuracy, whereas deep learning algorithms can do so with 91% accuracy. This research study analyzes the most recent deep learning-based breast cancer models detection and classification and present them through a comparative study. Additionally, to make it easier for any future experiments and comparisons, the datasets that are used and available to usage are listed in this research work. Models based on decision trees, random forests, logistic regression, and support vector machines are the most up-to-date, most accurate models used in machine learning techniques