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Deep Learning-Based Artificial Intelligence for Mammography.

Jung Hyun Yoon¹, Eun Kyung Kim²

¹Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Seoul, Korea.

Korean Journal of Radiology

|May 14, 2021

Summary

This summary is machine-generated.

Artificial intelligence (AI) shows promise in mammography for breast cancer detection and risk prediction. Further research is needed to confirm AI

Keywords:

Artificial intelligence Breast cancer Computer-aided diagnosis Deep learning Mammography

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Area of Science:

Radiology
Medical Imaging
Artificial Intelligence

Background:

Computer-aided mammography interpretation has been researched for a decade.
Deep learning technology has advanced AI applications in medical imaging.

Purpose of the Study:

To review the application of AI algorithms in mammography interpretation.
To discuss current challenges in implementing AI in clinical practice.

Main Methods:

Review of existing literature on AI in mammography.
Analysis of AI algorithm capabilities in density assessment, cancer detection, and risk prediction.

Main Results:

AI algorithms demonstrate promising results in quantitative assessment of parenchymal density.
AI shows potential in breast cancer detection, diagnosis, and risk prediction.
AI may improve interpretation workflow efficiency by reducing workload and time.

Conclusions:

AI-based algorithms offer potential for more precise patient management in mammography.
Further in-depth investigation is required to conclusively establish the effectiveness of AI algorithms.
Implementation of AI in real-world mammography practice faces several challenges.