What is data augmentation in healthcare?
An example of an AI chatbot conversation about data augmentation in healthcare.
What is data augmentation in healthcare?
Data augmentation in healthcare refers to techniques used to increase the diversity of training datasets by applying various transformations to existing data.
Can you give me some examples of data augmentation techniques?
Sure! Common techniques include rotation, flipping, scaling of images, and adding noise to medical images.
How does data augmentation improve machine learning models?
It helps models generalize better by providing more varied training data, reducing overfitting and improving accuracy.
Are there any specific applications of data augmentation in medical imaging?
Yes, it's widely used in areas like radiology, pathology, and dermatology to enhance image datasets for better diagnostic models.
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