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/PRNewswire/ -- The "Voice Communication Control System Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028F" report has been...
Nursing staff record observations about older people under their care in free-text nursing notes. These notes contain older people's care needs, disease symptoms, frequency of symptom occurrence, nursing actions, etc. Therefore, it is vital to develop a technique to uncover important data from these notes. This study developed and evaluated a deep learning and transfer learning-based named entity recognition (NER) model for extracting symptoms of agitation in dementia from the nursing notes. We employed a Clinical BioBERT model for word embedding. Then we applied bidirectional long-short-...
Dublin, Feb. 07, 2024 (GLOBE NEWSWIRE) -- The
Malnutrition is a severe health problem that is prevalent in older people residing in residential aged care facilities. Recent advancements in machine learning have made it possible to extract key insight from electronic health records. To date, few researchers applied these techniques to classify nursing notes automatically. Therefore, we propose a model based on ClinicalBioBert to identify malnutrition notes. We evaluated our approach with two mainstream approaches. Our approach had the highest F1-score of 0.90.
Natural Language Processing (NLP) is a powerful technique for extracting valuable information from unstructured electronic health records (EHRs). However, a prerequisite for NLP is the availability of high-quality annotated datasets. To date, there is a lack of effective methods to guide the research effort of manually annotating unstructured datasets, which can hinder NLP performance. Therefore, this study develops a five-step workflow for manually annotating unstructured datasets, including (1) annotator training and familiarising with the text corpus, (2) vocabulary identification, (3) anno...