Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care

Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care

Abstract Background The aim of our study was to determine whether the application of machine learning could predict PASC by using diagnoses from primary care and prescribed medication 1 year prior to PASC diagnosis. Methods This population-based case–control study included subjects aged 18–65 years...

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Main Authors: Seika Lee, Marta A. Kisiel, Pia Lindberg, Åsa M. Wheelock, Anna Olofsson, Julia Eriksson, Judith Bruchfeld, Michael Runold, Lars Wahlström, Andrei Malinovschi, Christer Janson, Caroline Wachtler, Axel C. Carlsson
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Medicine
Subjects:
Post-acute sequelae of COVID- 19 (PASC)
COVID- 19
Primary care
Machine learning
Stochastic gradient boosting
Online Access:https://doi.org/10.1186/s12916-025-04050-w
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https://doi.org/10.1186/s12916-025-04050-w

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