Monitoring of COVID-19 pandemic-related psychopathology using machine learning.

IF 3.8 4区 医学 Q1 Medicine Acta Neuropsychiatrica Pub Date : 2022-06-01 Epub Date: 2022-01-19 DOI:10.1017/neu.2022.2
Kenneth C Enevoldsen, Andreas A Danielsen, Christopher Rohde, Oskar H Jefsen, Kristoffer L Nielbo, Søren D Østergaard
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Abstract

The COVID-19 pandemic is believed to have a major negative impact on global mental health due to the viral disease itself as well as the associated lockdowns, social distancing, isolation, fear, and increased uncertainty. Individuals with preexisting mental illness are likely to be particularly vulnerable to these conditions and may develop outright 'COVID-19-related psychopathology'. Here, we trained a machine learning model on structured and natural text data from electronic health records to identify COVID-19 pandemic-related psychopathology among patients receiving care in the Psychiatric Services of the Central Denmark Region. Subsequently, applying this model, we found that pandemic-related psychopathology covaries with the pandemic pressure over time. These findings may aid psychiatric services in their planning during the ongoing and future pandemics. Furthermore, the results are a testament to the potential of applying machine learning to data from electronic health records.

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利用机器学习监测COVID-19大流行相关精神病理。
据信,由于病毒性疾病本身以及相关的封锁、社交距离、隔离、恐惧和不确定性增加,COVID-19大流行对全球心理健康产生了重大负面影响。先前存在精神疾病的人可能特别容易受到这些疾病的影响,并可能直接发展为“与covid -19相关的精神病理学”。在这里,我们在电子健康记录的结构化和自然文本数据上训练了一个机器学习模型,以识别在丹麦中部地区精神科服务中心接受治疗的患者中与COVID-19大流行相关的精神病理学。随后,应用该模型,我们发现,随着时间的推移,与大流行相关的精神病理学随大流行压力而变化。这些发现可能有助于精神科服务在当前和未来流行病期间的规划。此外,研究结果证明了将机器学习应用于电子健康记录数据的潜力。
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来源期刊
Acta Neuropsychiatrica
Acta Neuropsychiatrica 医学-精神病学
CiteScore
8.50
自引率
5.30%
发文量
30
审稿时长
6-12 weeks
期刊介绍: Acta Neuropsychiatrica is an international journal focussing on translational neuropsychiatry. It publishes high-quality original research papers and reviews. The Journal''s scope specifically highlights the pathway from discovery to clinical applications, healthcare and global health that can be viewed broadly as the spectrum of work that marks the pathway from discovery to global health.
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