Monitoring of COVID-19 pandemic-related psychopathology using machine learning.
Acta Neuropsychiatr
; 34(3): 148-152, 2022 Jun.
Article
de En
| MEDLINE
| ID: mdl-35042568
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.
Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
COVID-19
/
Troubles mentaux
Type d'étude:
Diagnostic_studies
/
Prognostic_studies
Limites:
Humans
Langue:
En
Journal:
Acta Neuropsychiatr
Année:
2022
Type de document:
Article
Pays d'affiliation:
Danemark