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Artificial Intelligence in Breast Cancer Screening ; INTELIGENCIA ARTIFICIAL NO RASTREIO DO CANCRO DA MAMA

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  • Additional Information
    • Contributors:
      Tavares, Catarina Maria Miranda da Silva
    • Publication Date:
      2025
    • Collection:
      Universidade de Coimbra: Estudo Geral
    • Abstract:
      Trabalho Final do Mestrado Integrado em Medicina apresentado à Faculdade de Medicina ; Breast cancer (BC) is the most frequently diagnosed malignancy and the second leading cause of cancer-related mortality among women worldwide. Mammographic screening has significantly contributed to early BC detection, along with reduced mortality, especially in high-income countries. However, discrepancies persist in low- and middle-income countries due to limited access to diagnostic and treatment resources. Furthermore, conventional methods, such as mammography, digital breast tomosynthesis (DBT), ultrasound, and magnetic resonance imaging (MRI), have some limitations. The integration of Artificial Intelligence (AI) into BC screening programs has emerged as a promising strategy to enhance early detection, improve diagnostic accuracy, and optimise screening programs. This literature review explores the current state of AI applications in BC screening, highlighting the strengths, challenges, and future prospects in this field. This review was conducted in the PubMed database, identifying 53 relevant studies published between 2014 and 2024.The findings highlight the potential of AI tools to increase sensitivity, specificity, demonstrating performance comparable to radiologists. Combination of radiologists with AI systems has shown to improve BC detection rates, along with reducing radiologist workload. However, ethical and legal concerns, such as algorithmic transparency, data privacy and accountability, still restrict widespread clinical implementation.In conclusion, AI integration into screening programs offers promising opportunities. However, there is a need for collaboration among clinicians and computer scientists, along with the regulation of AI systems to ensure their reliability, safety and clinical efficiency are essential. ; O cancro da mama é a neoplasia maligna mais frequentemente diagnosticada e a segunda principal causa de mortalidade relacionada com o cancro em mulheres a nível mundial. O rastreio mamográfico ...
    • Relation:
      https://hdl.handle.net/10316/119571; 203983998
    • Online Access:
      https://hdl.handle.net/10316/119571
    • Rights:
      info:eu-repo/semantics/openAccess
    • Accession Number:
      edsbas.7C654336