Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning.

• Published in: PLOS Neglected Tropical Diseases
• Main Authors: Sheng-Wen Huang, Huey-Pin Tsai, Su-Jhen Hung, Wen-Chien Ko, Jen-Ren Wang
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science (PLoS) 2020
• Subjects: Arctic medicine. Tropical medicine; RC955-962; Public aspects of medicine; RA1-1270; Arctic; Kung
• Online Access: https://doi.org/10.1371/journal.pntd.0008960; https://doaj.org/article/f009dfb28e37483292e837366d49e784

Background Dengue virus causes a wide spectrum of disease, which ranges from subclinical disease to severe dengue shock syndrome. However, estimating the risk of severe outcomes using clinical presentation or laboratory test results for rapid patient triage remains a challenge. Here, we aimed to dev...