Advances in the application of artificial intelligence in cancer diagnosis and treatment: A systematic review

Abstract

Artificial intelligence (AI) is revolutionizing cancer diagnosis and treatment by overcoming the limitations of traditional approaches. This systematic review, based on studies published between 2020 and 2024, analyzes AI’s impact in various oncological areas, emphasizing its role in early detection, personalized treatments, and optimization of clinical processes. Through deep and machine learning algorithms, AI has proven effective in interpreting medical images, analyzing multi-omics data, and detecting biomarkers. For example, in breast cancer, a hybrid model achieved 98.06% accuracy in tissue classification, while in colorectal cancer, pre-surgical detection improved with an Area Under the Curve (AUC) of 0.832. Additionally, AI has reduced radiotherapy planning times, facilitating treatment access in developing countries. However, challenges remain, such as the lack of standardization, the need for extensive data, and ethical concerns related to privacy and equity. Despite these barriers, recent advances underline AI’s transformative potential to improve diagnostic accuracy, therapeutic efficiency, and accessibility in cancer care. This study concludes that integrating AI could redefine cancer care but requires sustained efforts to address its limitations and ensure ethical and equitable application.