Identification of Breast Cancer Using Machine Learning Algorithm
A. Ramathilagam, Sundararajan Edwin Raja, V. P., P. Gopikannan, Raghavan P, Jayapriya M · 2024
In the modern era, the prevalence of various diseases is a significant concern, with cancer being among the most severe. Cancer, including types like lung, blood, nerve, cardiac, and breast cancer, contributes substantially to global mortality rates, accounting for approximately 1 in 6 deaths in 2018. The treatments for cancer, such as surgery and radiation therapy, play a crucial role in managing the disease and improving patient outcomes. However, there is a persistent need to reduce mortality rates further by leveraging advancements in machine learning techniques and algorithms, along with traditional medical interventions like medicines and surgical procedures. These innovations hold the potential to not only enhance cancer treatment but also improve diagnosis and patient satisfaction across a spectrum of diseases, highlighting the transformative impact of AI in healthcare. Furthermore, AI’s ongoing applications in healthcare have demonstrated promising results, although they come with certain limitations and challenges. Despite these challenges, the future possibilities of AI in disease management, personalized medicine, and patient care are vast. By exploring and integrating AI into healthcare systems, we can pave the way for more effective treatments better infection the executives procedures, and eventually, worked on understanding results and personal satisfaction across different ailments past disease.