Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Building a Cardiovascular Disease Prediction Model for Smartwatch Users Using Machine Learning: Based on the Korea National Health and Nutrition Examination Survey

Authors
Kim, Min-Jeong
Issue Date
Jul-2021
Publisher
MDPI
Keywords
smartwatch; cardiovascular disease prediction model; machine learning; logistic regression; artificial neural network; support vector machines; Korea National Health and Nutrition Examination Survey
Citation
BIOSENSORS-BASEL, v.11, no.7
Journal Title
BIOSENSORS-BASEL
Volume
11
Number
7
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/146523
DOI
10.3390/bios11070228
ISSN
2079-6374
Abstract
Smartwatches have the potential to support health care in everyday life by supporting self-monitoring of health conditions and personal activities. This paper aims to develop a model that predicts the prevalence of cardiovascular disease using health-related data that can be easily measured by smartwatch users. To this end, the data corresponding to the health-related data variables provided by the smartwatch are selected from the Korea National Health and Nutrition Examination Survey. To classify the prevalence of cardiovascular disease with these selected variables, we apply logistic regression, artificial neural network, and support vector machine among machine learning classification techniques, and compare the appropriateness of the algorithm through classification performance indicators. The prediction model using support vector machine showed the highest accuracy. Next, we analyze which structures or parameters of the support vector machine contribute to increasing accuracy and derive the importance of input variables. Since it is very important to diagnose cardiovascular disease early correctly, we expect that this model will be very useful if there is a tool to predict whether cardiovascular disease develops or not.
Files in This Item
There are no files associated with this item.
Appears in
Collections
사회과학대학 > 소비자경제학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Min Jeong photo

Kim, Min Jeong
사회과학대학 (소비자경제학과)
Read more

Altmetrics

Total Views & Downloads

BROWSE