<ul><li>Researchers have developed a prediction model for patient disposition using EF-Net.</li><li>The model incorporates categorical and numerical features to achieve higher accuracy.</li><li>The EF-Net model achieved an accuracy of 95.33%, while the Ensemble Model achieved 96%.</li><li>The experiment shows that EF-Net outperforms existing works in accuracy, AUROC, and F1-Score.</li></ul>

EF-Net: A Deep Learning Approach Combining Word Embeddings and Feature Fusion for Patient Disposition Analysis

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