Machine learning model to extract malnutrition data from nursing notes

M. Alkhalaf; M. Yin; C. Deng; Hui-Chen (Rita) Chang; P. Yu

doi:10.3233/SHTI231240

Machine learning model to extract malnutrition data from nursing notes

M. Alkhalaf, M. Yin, C. Deng, Hui-Chen (Rita) Chang, P. Yu

Western Sydney University

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	1452-1453
Number of pages	2
Journal	Studies in Health Technology and Informatics
Volume	310
DOIs	https://doi.org/10.3233/SHTI231240
Publication status	Published - 25 Jan 2024

Bibliographical note

Publisher Copyright:
© 2024 International Medical Informatics Association (IMIA) and IOS Press.

Open Access - Access Right Statement

© 2024 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/).

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10.3233/SHTI231240

Cite this

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abstract = "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.",

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AU - Deng, C.

AU - Chang, Hui-Chen (Rita)

AU - Yu, P.

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AB - 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.

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JO - Studies in Health Technology and Informatics

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Machine learning model to extract malnutrition data from nursing notes

Abstract

Bibliographical note

Open Access - Access Right Statement

UN SDGs

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