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Concept Check

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In disease diagnosis prediction, which technique is used for handling imbalanced datasets?

SMOTE oversampling technique

Random oversampling method

Undersampling approach

Class weighting strategy

What metric is crucial to minimize false negatives in disease prediction models?

F1-score value

Precision ratio

Accuracy percentage

Recall or sensitivity score

Which method prevents overfitting in neural networks for disease prediction?

Data augmentation process

Early stopping mechanism

L1 regularization technique

Dropout regularization layer

What is a key challenge in data privacy for disease diagnosis projects?

Model interpretability concerns

Data scarcity issues

Compliance with HIPAA regulations

Feature engineering complexities

Which model is ideal for image-based disease diagnosis in real-world projects?

Decision tree classifiers

Support vector machines

Recurrent neural networks

Convolutional neural networks

PreviousClassification Methods in Supervised Learning