AI and Machine Learning in Breast Cancer: Advancing Precision Medicine Through Data-Driven Models

Artificial Intelligence (AI) and Machine Learning (ML) advancements have revolutionized precision medicine, offering transformative breast cancer diagnosis and treatment solutions. By leveraging vast datasets, AI-powered models provide enhanced accuracy in tumor detection, classification, and prognosis, surpassing traditional diagnostic methods. Machine learning algorithms, including deep learning networks, uncover intricate patterns within imaging, genomic, and clinical data, enabling personalized treatment strategies. This paper highlights the integration of AI in breast cancer care, discussing state-of-the-art techniques, challenges in clinical implementation, and future opportunities. Through a comparative analysis of data-driven models, we demonstrate their potential to optimize early detection, improve patient outcomes, and support oncologists in decision-making processes.Artificial Intelligence (AI) and Machine Learning (ML) advancements have revolutionized precision medicine, offering transformative breast cancer diagnosis and treatment solutions. By leveraging vast datasets, AI-powered models provide enhanced accuracy in tumor detection, classification, and prognosis, surpassing traditional diagnostic methods. Machine learning algorithms, including deep learning networks, uncover intricate patterns within imaging, genomic, and clinical data, enabling personalized treatment strategies. This paper highlights the integration of AI in breast cancer care, discussing state-of-the-art techniques, challenges in clinical implementation, and future opportunities. Through a comparative analysis of data-driven models, we demonstrate their potential to optimize early detection, improve patient outcomes, and support oncologists in decision-making processes.

کلیدواژه ها:

Breast Cancer ، Machine Learning ، Artificial Intelligence ، Tumor Detection ، Precision Medicine