INNOVATIVE APPROACHES TO EARLY DETECTION AND PREDICTION OF TREATMENT OUTCOMES IN ONCOLOGY BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES

Abstract

Cancer remains one of the leading causes of morbidity and mortality worldwide, emphasizing the need for effective strategies aimed at early diagnosis and individualized treatment planning. The integration of artificial intelligence (AI) technologies into oncology has opened new opportunities for enhancing diagnostic accuracy, predicting treatment outcomes, and optimizing therapeutic decision-making. This article explores innovative approaches that utilize AI algorithms for the early detection of oncological diseases and the prognostic assessment of therapy effectiveness. The study highlights the role of machine learning and deep learning models in analyzing large datasets, identifying hidden patterns, and supporting clinical decisions. The implementation of AI-based systems in oncological practice not only improves diagnostic precision but also contributes to personalized and evidence-based medicine. The research underlines the importance of multidisciplinary collaboration and ethical considerations in the adoption of AI technologies for improving cancer care outcomes.