A Survey on Breast Cancer Prediction using Various Deep Learning and Machine Learning Techniques
G. Gurupakkiam, M. Ilayaraja · 2024
Breast Cancer continues to be a predominant contributor to mortality associated with cancer among women on a global scale. To improve survival rates and treatment consequences, it's necessary to detect issues early and create an accurate diagnosis. In recent years, Machine Learning (ML) and Deep Learning (DL) techniques have shown great promise in medical diagnostics, offering the potential to enhance the accuracy and efficiency of breast cancer detection and prognosis. This research work provides breast cancer prediction using deep learning and machine learning studies on mammograms, ultrasounds, magnetic resonance imaging, and digital pathology images conducted over the past decade. An evaluation of studies from the past ten years highlights how important deep learning and machine learning have been in better patient outcomes and enlarges the accuracy of breast cancer detection. The automation of medical image assessment, machine learning, and deep learning technologies facilitate radiologists and pathologists in rendering more knowledgeable and accurate decisions. This reduction in the probability of human errors culminates in superior diagnostic accuracy and treatment methodologies, thereby ultimately improving the quality of patient care.