Risk Assessment of Pregnancy-induced Hypertension Using a Machine Learning Approach

2021 ◽  
Author(s):  
Sirinat Wanriko ◽  
Narit Hnoohom ◽  
Konlakom Wongpatikaseree ◽  
Anuchit Jitpattanakul ◽  
Olarik Musigavong
Keyword(s):  
Machine Learning ◽  
Risk Assessment ◽  
Learning Approach ◽  
Pregnancy Induced Hypertension ◽  
Machine Learning Approach ◽  
Induced Hypertension

scholarly journals Development of Health Parameter Model for Risk Prediction of CVD Using SVM

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
P. Unnikrishnan ◽  
D. K. Kumar ◽  
S. Poosapadi Arjunan ◽  
H. Kumar ◽  
P. Mitchell ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Assessment ◽  
Sensitivity And Specificity ◽  
Assessment Model ◽  
Support Vector ◽  
Learning Approach ◽  
Framingham Study ◽  
Local Database ◽  
Machine Learning Approach ◽  
Health Parameters

Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared the parameters from the Framingham equation with linear regression analysis to establish the effect of training of the model for the local database. Support vector machine was used to determine the effectiveness of machine learning approach with the Framingham health parameters for risk assessment of cardiovascular disease (CVD). The result shows that while linear model trained using local database was an improvement on Framingham model, SVM based risk assessment model had high sensitivity and specificity of prediction of CVD. This indicates that using the health parameters identified using Framingham study, machine learning approach overcomes the low sensitivity and specificity of Framingham model.

A machine learning approach to risk assessment for alcohol withdrawal syndrome

2020 ◽  
Vol 35 ◽  
pp. 61-70
Author(s):  
Gerrit Burkhardt ◽  
Kristina Adorjan ◽  
Joseph Kambeitz ◽  
Lana Kambeitz-Ilankovic ◽  
Peter Falkai ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Assessment ◽  
Alcohol Withdrawal ◽  
Withdrawal Syndrome ◽  
Alcohol Withdrawal Syndrome ◽  
Learning Approach ◽  
Machine Learning Approach
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