Decision-making model for early diagnosis of congestive heart failure using rough set and decision tree approaches

Journal of Biomedical Informatics
Chang-Sik SonMin-Soo Kim

Abstract

The accurate diagnosis of heart failure in emergency room patients is quite important, but can also be quite difficult due to our insufficient understanding of the characteristics of heart failure. The purpose of this study is to design a decision-making model that provides critical factors and knowledge associated with congestive heart failure (CHF) using an approach that makes use of rough sets (RSs) and decision trees. Among 72 laboratory findings, it was determined that two subsets (RBC, EOS, Protein, O2SAT, Pro BNP) in an RS-based model, and one subset (Gender, MCHC, Direct bilirubin, and Pro BNP) in a logistic regression (LR)-based model were indispensable factors for differentiating CHF patients from those with dyspnea, and the risk factor Pro BNP was particularly so. To demonstrate the usefulness of the proposed model, we compared the discriminatory power of decision-making models that utilize RS- and LR-based decision models by conducting 10-fold cross-validation. The experimental results showed that the RS-based decision-making model (accuracy: 97.5%, sensitivity: 97.2%, specificity: 97.7%, positive predictive value: 97.2%, negative predictive value: 97.7%, and area under ROC curve: 97.5%) consistently outperformed th...Continue Reading

References

Mar 19, 1999·Artificial Intelligence in Medicine·J Komorowski, A Ohrn
Dec 6, 2005·Cardiology Clinics·Robert L RogersStephen S Gottlieb
Aug 9, 2006·Computer Methods and Programs in Biomedicine·Xiangyang WangXiaojun Liu
Feb 5, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·H M LeeY L Jou
Aug 4, 2009·Journal of Biomedical Informatics·Yonghong PengJianmin Jiang

❮ Previous
Next ❯

Citations

Aug 15, 2014·Journal of Medical Systems·Mahyar Taghizadeh NoueiSomayeh Ghazalbash
Nov 10, 2013·Journal of the American Medical Informatics Association : JAMIA·Chaitanya ShivadeAlbert M Lai
Jan 18, 2016·Computer Methods and Programs in Biomedicine·Daniel Ruiz-FernándezEddy Triana Palencia
May 22, 2016·Computer Methods and Programs in Biomedicine·Zerina Masetic, Abdulhamit Subasi
Mar 26, 2014·Journal of Biomedical Informatics·Alex Alexandridis, Eva Chondrodima
Aug 2, 2017·Health Informatics Journal·Ilham KadiJosé Luis Fernandez-Aleman
Apr 30, 2013·Healthcare Informatics Research·Sun-Ju JungYoon-Nyun Kim
Dec 2, 2017·Current Opinion in Cardiology·Saqib Ejaz AwanGirish Dwivedi
Nov 27, 2015·BMC Medical Informatics and Decision Making·Eleazar Gil-HerreraBenjamin Djulbegovic
Dec 14, 2018·Journal of Medical Systems·H BenharJ L Fernández-Alemán
Sep 22, 2020·Computer Methods in Biomechanics and Biomedical Engineering·Ahmet Çınar, Seda Arslan Tuncer
Feb 3, 2021·Mathematical Biosciences and Engineering : MBE·Lal HussainJalal S Alowibdi
Jun 15, 2020·European Journal of Clinical Investigation·Gary TseQingpeng Zhang

❮ Previous
Next ❯

Related Concepts

Related Feeds

Cardiovascular Diseases: Risk Factors

Cardiovascular disease is a significant health concern. Risk factors include hypertension, obesity, dyslipidemia and smoking. Women who are postmenopausal are at an increased risk of heart disease. Here is the latest research for risk factors of cardiovascular disease.

© 2021 Meta ULC. All rights reserved