Litcius/Paper detail

Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method

Jiun‐Chi Huang, Yi‐Chun Tsai, Pei-Yu Wu, Yu-Hui Lien, Chih-Yi Chien, Chih-Feng Kuo, Chih-Feng Kuo, Jeng-Fung Hung, Szu‐Chia Chen, Chao‐Hung Kuo, Chao‐Hung Kuo

2020Computer Methods and Programs in Biomedicine167 citationsDOI

Topics & Concepts

Random forestLasso (programming language)Regression analysisRegressionLinear regressionSupport vector machineComputer scienceStatisticsBlood pressureHemodialysisMathematicsMedicineArtificial intelligenceInternal medicineWorld Wide WebHemodynamic Monitoring and TherapyDialysis and Renal Disease ManagementHeart Failure Treatment and Management
Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method | Litcius