Huang, Hung LingHung LingHuangLee, Jung YuJung YuLeeLo, Yu ShuYu ShuLoLiu, I HsinI HsinLiuHuang, Sing HanSing HanHuangHuang, Yu WeiYu WeiHuangMENG-RUI LEELee, Chih HsinChih HsinLeeCheng, Meng HsuanMeng HsuanChengLu, Po LiangPo LiangLuJANN-YUAN WANGYang, Jinn MoonJinn MoonYangChong, Inn WenInn WenChong2022-11-012022-11-012022-09-141058-4838https://scholars.lib.ntu.edu.tw/handle/123456789/624351Systemic drug reaction (SDR) is a major safety concern with weekly rifapentine plus isoniazid for 12 doses (3HP) for latent tuberculosis infection (LTBI). Identifying SDR predictors and at-risk participants before treatment can improve cost-effectiveness of the LTBI program.eninterpretable machine learning; latent tuberculosis infection; rifapentine; systemic drug reaction; transcriptomeWhole-Blood 3-Gene Signature as a Decision Aid for Rifapentine-based Tuberculosis Preventive Therapyjournal article10.1093/cid/ciac003349898012-s2.0-85138444672WOS:000785714500001https://api.elsevier.com/content/abstract/scopus_id/85138444672