COVID-19 outcome prediction by integrating clinical and metabolic data using machine learning algorithms

• Main Authors: Karen E. Villagrana-Bañuelos (Author), Valeria Maeda-Gutiérrez (Author), Vanessa Alcalá-Rmz (Author), Juan J. Oropeza-Valdez (Author), Ana S. Herrera-Van Oostdam (Author), Julio E. Castañeda-Delgado (Author), Jesús Adrián López (Author), Juan C. Borrego Moreno (Author), Carlos E. Galván-Tejada (Author), Jorge I. Galván-Tejeda (Author), Hamurabi Gamboa-Rosales (Author), Huizilopoztli Luna-García (Author), José M. Celaya-Padilla (Author), Yamilé López-Hernández (Author)
• Format: Book
• Published: Permanyer, 2022-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Background: The coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus and is responsible for nearly 6 million deaths worldwide in the past 2 years. Machine learning (ML) models could help physicians in identifying high-risk individuals. Objectives: To study the use o...