Early Detection of Breast Cancer using Machine Learning
N. Manjunathan, N. Gomathi, S. Muthulingam · 2023
Globally, Breast cancer is one of the most common types of cancer in women. Additional research is required to address the challenges and limitations of traditional detection process, as well as to create standardized processes for data collection and analysis of breast cancer by utilizing mammograms and other medical imaging data. Several research has been undertaken in recent years to create and assess ML models for breast cancer diagnosis, recurrence prediction, and therapy planning. Machine learning algorithms may also be trained to recognize small changes in breast tissue that may be symptomatic of cancer, even before a tumor can be seen on a mammogram, as done traditionally. The application of ML approaches in breast cancer diagnosis has resulted in higher accuracy and specificity, making it a suitable tool for assisting clinicians in clinical decision-making. Overall, the findings indicate that more study may be required to address the problems and limitations of ML in breast cancer diagnosis, as well as to create standardized processes for data collection and analysis.