Artificial intelligence for breast cancer screening: Opportunity or hype?

Area of Science:

• Radiology
• Medical Imaging
• Artificial Intelligence in Healthcare

Background:

• Mammography screening for breast cancer (BC) offers mortality benefits but faces challenges with missed cancers and false positives.
• Current efforts to improve screening focus on intensifying imaging, increasing costs and potential harms.
• There is a need for more efficient and 'smarter' mammography screening practices.

Purpose of the Study:

• To explore the potential of artificial intelligence (AI) in enhancing breast cancer detection through mammography.
• To discuss the current reality and future promise of AI in mammography screening.
• To consider the implications of AI adoption in breast cancer diagnostics.

Main Methods:

• Review of current practices in mammography screening.
• Analysis of artificial intelligence capabilities in image interpretation.
• Discussion of the potential benefits and unintended consequences of AI in breast cancer detection.

Main Results:

• Artificial intelligence demonstrates advanced learning capabilities with large datasets for image interpretation.
• AI has the potential to improve the efficiency and accuracy of breast cancer detection.
• Unintended consequences of AI in BC detection require careful consideration and research.

Conclusions:

• AI presents a promising avenue for making mammography screening smarter and more efficient.
• Further research is needed to understand and mitigate potential unintended consequences of AI in BC detection.
• The integration of AI in mammography holds significant potential for improving breast cancer outcomes.