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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Are artificial intelligence systems useful in breast cancer screening programs?

O Díaz1, A Rodríguez-Ruiz2, A Gubern-Mérida2

  • 1Departamento de Matemáticas e Informática, Universidad de Barcelona, Barcelona, España.

Radiologia
|January 19, 2021
PubMed
Summary

Population-based breast cancer screening programs effectively reduce mortality using mammography. Artificial intelligence systems show promise for improving diagnostic accuracy and reducing false positives compared to traditional computer-assisted diagnosis (CAD).

Keywords:
Aprendizaje profundoArtificial intelligenceBreast cancer screeningCADCribado de cáncer de mamaDeep learningInteligencia artificialMammographyMamografía

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Oncology

Background:

  • Population-based breast cancer screening programs significantly reduce cancer mortality.
  • Mammography is the primary screening tool, with digital mammography enabling computer-assisted diagnosis (CAD).
  • Traditional CAD systems often yield high false positive rates, increasing radiologist workload and patient anxiety.

Purpose of the Study:

  • To explain the fundamentals of artificial intelligence (AI) systems.
  • To provide an overview of AI applications in breast cancer screening.
  • To highlight AI's potential to improve diagnostic performance over traditional CAD.

Main Methods:

  • Review of artificial intelligence principles relevant to medical imaging.
  • Analysis of existing studies on AI in breast cancer screening.
  • Comparison of AI diagnostic performance against traditional CAD systems.

Main Results:

  • Artificial intelligence systems demonstrate superior diagnostic performance compared to conventional CAD.
  • AI has the potential to enhance accuracy in breast cancer detection.
  • AI may help mitigate the issue of high false positive rates associated with CAD.

Conclusions:

  • AI systems offer a promising advancement for breast cancer screening programs.
  • AI can potentially improve radiologist efficiency and diagnostic accuracy.
  • Further implementation of AI in mammography screening warrants consideration.