Healthcare
Common Challenges
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1
Ensuring access to high-quality, labeled data is essential for training effective models, but acquiring and curating such data can be difficult and time-consuming.
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2
Striking the right balance in model complexity to avoid overfitting (model is too closely fit to the training data) and underfitting (model is too simple to capture the underlying patterns) is a persistent challenge.
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3
Machine learning, particularly deep learning, requires significant computational power and resources, which can be costly and environmentally taxing.
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4
Many machine learning models operate as “black boxes,” making it challenging to understand how they arrive at specific decisions or predictions.