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Machine learning algorithms along with computer-aided tools offer a platform for finding patterns beyond human perceptions. However, despite new developments in the field of AI and machine learning, and the development of new CAD tools, there are several challenges to execution in practical clinical environments.
This paper elaborates on some of these challenges and discusses the ways to address them by embracing widespread AI-based medical imaging.
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