Artificial intelligence in breast cancer screening: Current evidence and future perspectives for implementation in Serbia
Introduction: Breast cancer remains the most frequently diagnosed malignancy and one of the leading causes of cancer mortality among women worldwide. Despite the implementation of organized mammography screening programmes, considerable disparities in mortality persist, particularly in lowand middle-income countries. Artificial intelligence (AI) has emerged as a promising tool for improving the accuracy, efficiency, and accessibility of breast cancer screening. To review current evidence regarding the role of artificial intelligence in breast cancer screening and early detection, with particular emphasis on its potential application within the healthcare system of the Republic of Serbia. Methodology: A comprehensive literature review was conducted using the MEDLINE, PubMed, and KOBSON databases. Literature published between 2012 and 2026 were identified using the keywords breast cancer, artificial intelligence, mammography, screening, and machine learning. After applying predefined inclusion criteria, 23 relevant publications were included in the final analysis. Topic: Current evidence demonstrates that AI-assisted mammography achieves diagnostic performance comparable to or exceeding that of experienced breast radiologists, while substantially reducing reading workload. Prospective clinical trials have shown that AI-supported screening increases early cancer detection rates without compromising patient safety. Beyond lesion detection, AI enables individualized risk assessment, prediction of interval cancers, and supports the transition toward risk-adapted screening strategies. For Serbia, AI-assisted centralized triage systems could optimize limited radiology resources, improve access to expert interpretation, and strengthen organized screening programmes. Successful implementation, however, requires local validation studies, interoperable digital infrastructure, appropriate regulatory frameworks, and continuous professional education. Conclusion: Artificial intelligence has the potential to substantially improve breast cancer screening by increasing diagnostic accuracy, reducing radiologists' workload, and supporting personalized screening approaches. Strategic integration aligned with European quality standards and national healthcare priorities could promote earlier diagnosis and reduced breast cancer mortality in Serbia.