THE USE OF ARTIFICIAL INTELLIGENCE AS AN AID IN BREAST CANCER DIAGNOSIS
DOI:
https://doi.org/10.56238/arev7n9-200Keywords:
Artificial Intelligence, Diagnosis, Magnetic Resonance Imaging, Breast CancerAbstract
Artificial Intelligence has proven to be highly effective in assisting cancer diagnosis, including breast cancer. There are various tools that can be employed in this process, which facilitates the selection of the most efficient one depending on each specific case. Despite the advances, it is essential to understand its limitations and seek solutions to overcome them. This study aims to discuss the use of Artificial Intelligence as an auxiliary tool in cancer diagnosis. To this end, an integrative literature review was conducted between July and September 2025. The databases used were the Virtual Health Library (VHL) and the United States National Library of Medicine (PUBMED), with the following descriptors and MeSH terms: Artificial Intelligence, Diagnosis, Magnetic Resonance Imaging, and Breast Cancer. Inclusion criteria comprised full-text articles published in Portuguese, English, and Spanish between 2020 and 2025, with full availability. After the initial filtering, readings were conducted and exclusion criteria applied: duplicate articles, those unrelated to the proposed topic, parallel themes, editorials, and publications older than five years. A total of 39 articles were included for discussion among the authors. The use of AI has revolutionized breast cancer diagnosis through radiological image evaluation. Its application increases diagnostic accuracy and improves patients’ quality of life. The reduction of radiologists’ workload and the minimization of human errors are key advantages of these tools. Multimodal and radiomic models have shown promise in predicting chemotherapy response and lymph node status. It is important to emphasize that such tools require ongoing refinement and human supervision to correct and prevent potential errors. Thus, the advances brought by Artificial Intelligence are consolidating its role as a valuable ally in breast cancer diagnosis. Its use in medicine enhances decision-making efficiency but demands continuous improvement and validation by researchers and healthcare professionals. Strengthening the integration between AI and medical expertise is essential to ensure safety and accuracy in breast cancer diagnostics.
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