Deep Neural Network-Based Prediction of Breast Cancer Using Cloud Computing
S. Muthumanickam, Sukhpal Singh Gill · 2024
Breast cancer remains a formidable global health challenge, demanding innovative approaches for early detection, accurate diagnosis, and personalised treatment. This chapter seeks to leverage the power of artificial intelligence (AI) (especially deep learning) to enhance the understanding of breast cancer and transform its management landscape. The use of cutting-edge deep learning techniques enables exploration into the intricate world of breast cancer analysis using datasets and cloud computing resources. By training deep learning algorithms on the datasets, hidden patterns, correlations, and insights that hold the potential to redefine how to predict breast cancer are learned. The fusion of computational prowess with medical expertise has the potential to revolutionise breast cancer management, fostering earlier detection, tailored treatments, and improved patient outcomes. A comparison with conventional diagnostic approaches revealed a significant improvement in predicted accuracy, demonstrating the model&s;s superiority. The combination of modern deep learning approaches and the agility of cloud computing creates a game-changing opportunity for improving breast cancer prediction. Finally, this initiative emphasises deep learning&s;s revolutionary role in revolutionising breast cancer research and patient care. It contributes to current efforts to refine and personalise breast cancer diagnosis and therapy, with the ultimate objective of improving patient outcomes and decreasing the burden of this tough disease by highlighting the synergies between AI and medicine.