ML Basics
Machine learning uses algorithms to analyze imaging data. It identifies patterns that may be difficult for humans to detect. Students learn how ML supports radiology.
Training Models
Training requires large datasets and accurate labels. Proper training improves model performance. Students explore how datasets influence outcomes.
Clinical Applications
Machine learning supports detection of fractures, tumors, and abnormalities. It also helps prioritize urgent cases. Students learn common clinical uses.
Limitations
Machine learning models require careful validation. Bias and errors can affect performance. Students learn how to evaluate model reliability.
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