Khan Mohd Jawed, Singh Arun Kumar, Sultana Razia, Singh Pankaj Pratap, Khan Asif, Saxena Sandeep
Department of Computer Science & Engineering, Central Institute of Technology, Kokrajhar, Assam, India.
Department of Computer Science and Engineering, Greater Noida Institute of Technology, Greater Noida, India.
Cell Biochem Funct. 2023 Dec;41(8):996-1007. doi: 10.1002/cbf.3868. Epub 2023 Oct 9.
Breast cancer is the most common cancer among women globally and presents a significant challenge due to its rising incidence and fatality rates. Factors such as cultural, socioeconomic, and educational barriers contribute to inadequate awareness and access to healthcare services, often leading to delayed diagnoses and poor patient outcomes. Furthermore, fostering a collaborative approach among healthcare providers, policymakers, and community leaders is crucial in addressing this critical women's health issue, reducing mortality rates, alleviating, and the overall burden of breast cancer. The main goal of this review is to explore various techniques of machine learning algorithms to examine high accuracy and early detection of breast cancer for the safe health of women.
乳腺癌是全球女性中最常见的癌症,由于其发病率和死亡率不断上升,带来了重大挑战。文化、社会经济和教育障碍等因素导致对医疗服务的认知不足和获取机会有限,常常导致诊断延误和患者预后不佳。此外,促进医疗服务提供者、政策制定者和社区领袖之间的协作方法对于解决这一关键的女性健康问题、降低死亡率、减轻乳腺癌的总体负担至关重要。本综述的主要目标是探索各种机器学习算法技术,以实现乳腺癌的高精度早期检测,保障女性的健康安全。