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Predicting ICU Length of Stay for Patients using Latent Categorization of Health Conditions (2025.naacl-industry)

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Challenge: Traditional approaches to predicting the duration of a patient's stay in an Intensive Care Unit (ICU) rely on structured clinical data, but recent advances in language models offer significant potential to utilize unstructured text data for ICU length-of-stay (LoS) predictions.
Approach: They propose a method for analyzing nursing notes to predict ICU length-of-stay of patients.
Outcome: The proposed model outperforms baseline models on the MIMIC-III dataset and shows that it significantly outperformed existing models.

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