Predicting dry weight change in Hemodialysis patients using machine learning.

ABSTRACT:

Background

Machine Learning has been increasingly used in the medical field, including managing patients undergoing hemodialysis. The random forest classifier is a Machine Learning method that can generate high accuracy and interpretability in the data analysis of various diseases. We attempted to apply Machine Learning to adjust dry weight, the appropriate volume status of patients undergoing hemodialysis, which requires a complex decision-making process considering multiple indicators and the patient's physical conditions.

Methods

All medical data and 69,375 dialysis records of 314 Asian patients undergoing hemodialysis at a single dialysis center in Japan between July 2018 and April 2020 were collected from the electronic medical record system. Using the random forest cla

SUBMITTER: Inoue H 

PROVIDER: S-EPMC10308746 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature