Establishing a prediction model of severe acute mountain sickness using machine learning of support vector machine recursive feature elimination

Abstract excerpt

Severe acute mountain sickness (sAMS) can be life-threatening, but little is known about its genetic basis. The study was aimed to explore the genetic susceptibility of sAMS for the purpose of prediction, using microarray data from 112 peripheral blood mononuclear cell (PBMC) samples of 21 subjects, who were exposed to very high altitude (5260 m), low barometric pressure (406 mmHg), and hypobaric hypoxia (VLH) at...