학술논문

Feature Selection for Intradialytic Blood Pressure Value Prediction Using GRU-based Method Under RFECV algorithm
Document Type
Conference
Source
2021 9th International Conference on Orange Technology (ICOT) Orange Technology (ICOT), 2021 9th International Conference on. :1-4 Dec, 2021
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Linear regression
Predictive models
Logic gates
Feature extraction
Prediction algorithms
Blood pressure
Social implications of technology
Dialysis
Blood Pressure
RFECV
GRU
Feature Selection
Language
Abstract
Cardiovascular events is a common complication in dialysis patients and might has relation to intradialytic blood pressure (BP) variability. This study aimed to use the new method of feature selection to improve the performance of BP value prediction. We used feature importance by a different model to sort from high to low one by one, then we obtained the combination of feature values that have the highest accuracy for predictive power, which was later disclosed as BP. Later we compared recursive feature elimination with cross-validation (RFECV) mode with non-RFECV mode, both followed by gated recurrent units (GRU), to determine which is better in this clinical situation. The results showed that the former is more accurate both under , and the predictive power is better at 100–160 mmHg, especially around 130mmHg. Nevertheless, the BP prediction in clinical use should be applied according to individual condition of each patient.