Predictive models of hypertensive disorders in pregnancy based on support vector machine algorithm

Autor: Lin Yang, Hongqing Jiang, Ge Sun, Mingzhou Xu, Dongmei Hao, Xuwen Li, Yimin Yang, Jing Shao, Anran Wang, Song Zhang
Rok vydání: 2020
Předmět:
Pediatrics
Support vector machine algorithm
Support Vector Machine
Blood Pressure
Early pregnancy factor
02 engineering and technology
0302 clinical medicine
Pregnancy
Risk Factors
Prediction methods
Early prediction
Data Mining
Hematologic Tests
biology
Epidemiological Factors
machine learning
model research
Radial Artery
Female
Algorithms
Research Article
Information Systems
Adult
medicine.medical_specialty
0206 medical engineering
Biomedical Engineering
Biophysics
Gestational Age
Health Informatics
Bioengineering
Pulse Wave Analysis
Biomaterials
03 medical and health sciences
Predictive Value of Tests
medicine
Humans
business.industry
Body Weight
Hemodynamics
Hypertension
Pregnancy-Induced

medicine.disease
020601 biomedical engineering
Support vector machine
Early Diagnosis
Socioeconomic Factors
biology.protein
business
030217 neurology & neurosurgery
Predictive modelling
Zdroj: Technology and Health Care
ISSN: 1878-7401
0928-7329
Popis: BACKGROUND: The risk factors of hypertensive disorders in pregnancy (HDP) could be summarized into three categories: clinical epidemiological factors, hemodynamic factors and biochemical factors. OBJECTIVE: To establish models for early prediction and intervention of HDP. METHODS: This study used the three types of risk factors and support vector machine (SVM) to establish prediction models of HDP at different gestational weeks. RESULTS: The average accuracy of the model was gradually increased when the pregnancy progressed, especially in the late pregnancy 28–34 weeks and ⩾ 35 weeks, it reached more than 92%. CONCLUSION: Multi-risk factors combined with dynamic gestational weeks’ prediction of HDP based on machine learning was superior to static and single-class conventional prediction methods. Multiple continuous tests could be performed from early pregnancy to late pregnancy.
Databáze: OpenAIRE