Machine learning prediction model for treatment responders in patients with primary biliary cholangitis.

Naruhiro KimuraKazuya TakahashiToru SetsuShu GotoSuguru MiidaNobutaka TakedaYuichi KojimaYoshihisa AraoKazunao HayashiNorihiro SakaiYusuke WatanabeHiroyuki AbeHiroteru KamimuraAkira SakamakiTakeshi YokooKenya Kamimura Atsunori TsuchiyaShuji Terai

Published in: JGH open : an open access journal of gastroenterology and hepatology (2023)

ML algorithms could improve treatment response prediction using pretreatment data, which could lead to better prognoses. In addition, the ML model using XGB could predict the prognosis of patients before treatment initiation.

Keyphrases

machine learning
end stage renal disease
ejection fraction
newly diagnosed
deep learning
big data
prognostic factors
artificial intelligence
peritoneal dialysis
combination therapy