Publications by authors named "Marilia de Albuquerque Sena"
Article Synopsis
- A machine learning method was used to analyze genome polymorphisms for predicting severe COVID-19 outcomes in 96 Brazilian patients.
- The study identified 12 important SNPs using a support vector machine approach, achieving metrics of 85% accuracy, 80% sensitivity, and 90% specificity in classification.
- The findings indicate that genetic factors play a crucial role in determining the risk of developing severe COVID-19, including identifying individuals at risk even when they are not infected.
