Multisite study using a customised NLP model to predict disposition in the emergency department: protocol paper
Introduction To address timely care in emergency departments, artificial neural networks (ANNs) with natural language processing will be applied to triage notes to predict patient disposition. This study will develop a predictive model that predicts disposition and type of admission.Methods and anal...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2025-07-01
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| Series: | BMJ Health & Care Informatics |
| Online Access: | https://informatics.bmj.com/content/32/1/e101285.full |
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| Summary: | Introduction To address timely care in emergency departments, artificial neural networks (ANNs) with natural language processing will be applied to triage notes to predict patient disposition. This study will develop a predictive model that predicts disposition and type of admission.Methods and analysis This will include data preprocessing and quality enhancement, masked language modelling, ANN-based fusion network for prediction. Generative artificial intelligence, along with a medical dictionary, will be employed to augment and contextually reconstruct triage notes to disambiguate and improve linguistic quality. Text features will be extracted, and cluster analysis will be performed on the extracted topics and text features to identify distinct patterns. |
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| ISSN: | 2632-1009 |