Advancing cancer diagnosis and treatment: integrating image analysis and AI algorithms for enhanced clinical practice

• Published in: The Artificial intelligence review Vol. 58; no. 4; p. 105
• Main Authors: Saeidnia, Hamid Reza, Firuzpour, Faezeh, Kozak, Marcin, majd, Hooman Soleymani
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 25.01.2025; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Cancer; Computer Science; Deep learning; Diagnosis; Image analysis; Image processing; Image processing systems; Imaging techniques; Machine learning; Medical diagnosis; Medical imaging; R&D; Research & development; Image analysis; Cancer diagnosis; AI algorithms; Clinical practice; Artificial Intelligence; Cancer
• ISSN: 1573-7462; 0269-2821; 1573-7462
• DOI: 10.1007/s10462-025-11117-w

Cancer screening and diagnosis with the utilization of innovative Artificial Intelligence tools improved the treatment strategies and patients’ survival. With the rapid development of imaging technologies and the rise of artificial intelligence (AI), there is a significant opportunity to improve cancer diagnostics through the combination of image analysis and AI algorithms. This article provides a comprehensive review of studies that have investigated the application of AI-assisted image processing in cancer diagnosis. We searched the Web of Science and Scopus databases to identify relevant studies published between 2014 and January 2024. The search strategy utilized targeted keywords such as cancer diagnostics, image analysis, artificial intelligence, and advanced imaging techniques. We limited the review to articles written in English and using AI-assisted image processing in cancer diagnosis. The results show that by leveraging machine learning algorithms, including deep learning, computer-aided diagnosis systems have been developed that are efficient in detecting tumors, thereby facilitating early cancer detection. Additionally, various authors have explored the integration of personalized treatment approaches and precision medicine, allowing for the development of treatment plans tailored to individual patient characteristics and needs. The review emphasizes the potential of AI-assisted image processing in revolutionizing cancer diagnostics. The insights gained from this study contribute to the current understanding of the field and pave the way for future research and development aimed at advancing cancer diagnostics using image analysis and artificial intelligence.