In the context of healthcare, what is the significance of machine learning models being interpretable?
- To provide insights into the model's decision-making process and enable trust in medical applications
- To speed up the model training process
- To make models run on low-end hardware
- To reduce the amount of data required
Interpretable models are essential in healthcare to ensure that the decisions made by the model are understandable and can be trusted, which is crucial for patient safety and regulatory compliance.
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