Predicting a single HIV drug resistance measure from three international interpretation gold standards

作     者：Singh Yashik Mars Maurice 

作者机构：Department of TelehealthNelson R Mandela School of MedicineUniversity of KwaZulu-Natal719 Umbilo RoadUmbiloDurbanSouth Africa 

出 版 物：《Asian Pacific Journal of Tropical Medicine》 (亚太热带医药杂志（英文版）)

年 卷 期：2012年第5卷第7期

页      面：566-572页

核心收录：

学科分类：1004[医学-公共卫生与预防医学(可授医学、理学学位)] 1002[医学-临床医学] 100401[医学-流行病与卫生统计学] 10[医学] 

主　　题：Drug resistance Antiretroviral therapy Highly active HIV Artificial intelligence Expert systems 

摘      要：Objective:To investigate the possibility of combining the interpretation of three gold standard interpretation algorithms using weighted heuristics in order to produce a single resistancemeasure. Methods:The outputs of HIVdb,Rega,ANRS were combined to obtain a single resistance profile using the equally weighted voting algorithm,accuracy based weighing voting algorithm and the Bayesian based weighted voting algorithm ***:The Bayesian based voting combination increased the accuracy of the resistance profile prediction compared to phenotype,from 58%to 69%.The equal weighted voting algorithm and the accuracy based algorithm both increased the prediction accuracy to 60%.Conclusions:From the result obtained it is evident that combining the gold standard interpretation algorithms may increase the predictive ability of the individual interpretation algorithms.