Artificial intelligence for breast cancer: Implications for diagnosis and management
Jehad Feras AlSamhori, Abdel Rahman Feras AlSamhori, Leslie Anne Duncan, Ahmad Qalajo, Hamzeh Feras Alshahwan, Mohammed Al-abbadi, Mohammad Al Soudi, Rihane Zakraoui, Ahmad Feras AlSamhori, Saif Aldeen AlRyalat, Abdulqadir J. Nashwan
Abstract
Breast cancer's global impact and high mortality rates drive interest in Artificial intelligence (AI) applications. AI's pattern recognition and decision-making abilities offer promise in detection, diagnosis, personalized treatment, risk assessment, and prevention. Screening and early detection are improved by AI-enhanced mammography. AI aids radiologists in lesion detection and diagnosis, though concerns about false positives persist. In addition, AI revolutionizes breast imaging, assisting in reading mammograms, biomarker assessment, lymph node detection, and outcome prediction. Genetic insights into risk and treatment response are advanced by AI, particularly through deep learning algorithms. Collaborative treatment approaches benefit from AI-guided radiotherapy planning. However, challenges of AI include data privacy, ethics, and regulatory issues that must be navigated to ensure successful AI implementation while upholding healthcare trust. Therefore, this commentary provided an overview of implication of AI in breast cancer.