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Implement an LSTM model to improve anemia prediction by capturing sequential dependencies in pixel and Hb data, and compare its performance with existing models (Logistic Regression, Decision Tree, and Gradient Boosting).
Use Case
Adding the LSTM model will enhance the project by leveraging sequential data patterns, potentially improving prediction accuracy for anemia detection. It will also provide a deeper comparison between traditional machine learning models and deep learning approaches, offering insights into which method is best suited for this dataset.