Artificial Intelligence in Cancer Treatment

Abstract

The expanding role of AI in oncology, covering diagnostic imaging, personalized therapy, drug discovery, patient monitoring, and ethical considerations. The discussion also highlights real-world applications and future directions for integrating AI into global cancer care. AI plays a vital role in today’s medical technology, offering innovative ways to identify, manage, and monitor cancer by using data-driven computational models. Artificial intelligence (AI) is rapidly reshaping oncology by enabling earlier detection, improved diagnostic accuracy, personalized treatment planning, and accelerated drug discovery. This review synthesizes recent advances in machine learning (ML) and deep learning (DL) applications in cancer treatment, with emphasis on clinical decision support systems, radiomics, pathology image analysis, predictive modeling for therapy response, and integration of multimodal data for precision oncology. We discuss methodological considerations, regulatory and ethical challenges, and future directions including federated learning, explainable AI, and integration into clinical workflows. Representative studies and meta-analyses from 2020–2025 are summarized to provide clinicians and researchers a practical understanding of current capabilities and limitations of AI in cancer care.

Keywords: Artificial intelligence; machine learning; deep learning; radiomics; oncology; precision medicine; clinical decision support; immunotherapy prediction.