The study focuses on the use of machine learning techniques to detect persistent inflammatory biomarkers in post-COVID-19 patients. The research involved 290 patients, using data collected from hospitals in Iraq. The data included various clinical parameters, patient demographics, and treatment histories. Machine learning algorithms such as logistic regression, random forests, support vector machines, and gradient boosting were used to construct predictive models. These models demonstrated high accuracy and precision, highlighting the potential of machine learning in facilitating early diagnosis and personalized treatment strategies for individuals at risk of persistent inflammation.
Publication date: 28 Sep 2023
Project Page: https://www.isohe.org/medical-advances-and-innovations-journal
Paper: https://arxiv.org/pdf/2309.15838
