Keywords
Image diagnosis
Cancer
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Abstract
Objective: To describe the applicability of artificial intelligence in the medical field, specifically in diagnostic imaging. Methods: This is an integrative literature review with a qualitative and descriptive approach, based on studies published from January 2020 to May 2025. The search strategy followed the PICO model, focusing on cancer patients and the use of artificial intelligence in diagnostic imaging. Searches were conducted in the PubMed and Cochrane Library databases. Included were original studies published in English, Portuguese, or Spanish in peer-reviewed journals. Exclusion criteria were reviews, theses, dissertations, and articles not directly addressing the topic. Study selection followed three steps: screening titles, abstracts, and full texts, followed by quality assessment based on the Oxford Centre for Evidence-Based Medicine criteria. Results: Artificial intelligence demonstrated varied performance depending on the medical context, but overall showed a notable reduction in false positives and improvements in the detection rates of polyps and neoplasms. Its application across different types of cancer imaging contributed to greater diagnostic accuracy and efficiency, particularly in assisting less experienced professionals. Final considerations: AI presents significant potential to enhance diagnostic processes in oncology, especially in early detection, although its effectiveness still depends on the specific clinical context.
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