Have a personal or library account? Click to login
The Role of HMG COA Reductase Inhibitors on the Progression of Coronary Artery Disease: Focus on Prediction Model Cover

The Role of HMG COA Reductase Inhibitors on the Progression of Coronary Artery Disease: Focus on Prediction Model

Open Access
|Feb 2022

References

  1. 1. Teramukai S, Okuda Y, Miyazaki S, Kawamori R, Shirayama M, Teramoto T. Dynamic prediction model and risk assessment chart for cardiovascular disease based on on-treatment blood pressure and baseline risk factors. Hypertens Res. 2016 Feb; 39(2):113-8. doi: 10.1038/hr.2015.120. Epub 2015 Nov 26. PubMed PMID: 26606874; PubMed Central PMCID: PMC4753397.10.1038/hr.2015.120
  2. 2. Reiner Z. Primary prevention of cardiovascular disease with statins in the elderly. Curr Atheroscler Rep. 2014 Jul; 16(7):420.10.1007/s11883-014-0420-6
  3. 3. Titapiccolo JI, Ferrario M, Barbieri C, Marcelli D, Mari F, Gatti E, et al. Predictive modeling of cardiovascular complications in incident hemodialysis patients. Conf Proc IEEE Eng Med Biol Soc. 2012; 2012:3943–6.10.1109/EMBC.2012.6346829
  4. 4. Steyerberg EW, Harrell FE Jr, Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 2001; 54: 774–781.10.1016/S0895-4356(01)00341-9
  5. 5. ESH/ESC Task Force for the Management of Arterial Hypertension. 2013 Practice guidelines for the management of arterial hypertension of the European Society of Hypertension (ESH) and the European Society of Cardiology (ESC): ESH/ESC Task Force for the Management of Arterial Hypertension. J Hypertens 2013; 31: 1925–1938.10.1097/HJH.0b013e328364ca4c
  6. 6. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15: 361–387.10.1002/(SICI)1097-0258(19960229)15:4<;361::AID-SIM168>3.0.CO;2-4
  7. 7. Kononenko, I., Kukar, M., 2007. Machine Learning and Data Mining: Introduction to Principles and Algorithms. Horwood publm10.1533/9780857099440
  8. 8. Maimon. O., Rokach, L., 2005. Data Mining and Knowledge Discovery Handbook, Springer, Heidelberg.10.1007/b107408
  9. 9. De Graaf, M. A., Broersen, A., Ahmed, W., Kitslaar, P. H., Dijkstra, J., Kroft, L. J., Scholte, A. J., 2014. Feasibility of an Automated Quantitative Computed Tomography Angiography–Derived Risk Score for Risk Stratification of Patients With Suspected Coronary Artery Disease. The American Journal of Cardiology, 113(12):1947–1955. doi:10.1016/j.ajcard.2014.03.034.10.1016/j.amjcard.2014.03.034
  10. 10. Chawla, N., Bowyer, K., Hall, L., Kegelmeyer, W., 2002. SMOTE: Syntheticminority over-sampling technique. J. Artif. Intell. Res. 16:321–35710.1613/jair.953
  11. 11. Yijing, L., Haixiang, G., Xiao, L., Yanan, L., Jinling, L., 2016. Adapted ensemble classification algorithm based on multiple classifier system and feature selection for classifying multi-class imbalanced data. Knowl.-Based Syst. 94:88-104.10.1016/j.knosys.2015.11.013
  12. 12. Robnik-Sikonja, M., Kononenko, I., 1997. An adaptation of Relief for attribute estimation in regression. In: Fourteenth International Conference on Machine Learning. 296-304.
  13. 13. Peng, H., Long, F., Ding, C., 2005. Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 27 (8):1226-12 38.10.1109/TPAMI.2005.159
  14. 14. Kohavi, R., John, G., 1997. Wrapper for Feature Subset Selection. Artificial Intelligencel. 97 (1-2): 273-324. Doi:10.1016/S0004-3702(97)00043-X.10.1016/S0004-3702(97)00043-X
  15. 15. SMARTool EU Horizon 2020 project: Simulation Modeling of coronary ARTery disease: a tool for clinical decision support. Grant agreement ID: 689068, 2016-2019.
  16. 16. EVINCI EU FP7 Project: EValuation of INtegrated Cardiac Imaging. Grant agreement ID: 222915, 2009-2012
DOI: https://doi.org/10.2478/sjecr-2019-0024 | Journal eISSN: 2956-2090 | Journal ISSN: 2956-0454
Language: English
Page range: 309 - 316
Submitted on: May 26, 2019
|
Accepted on: May 31, 2019
|
Published on: Feb 2, 2022
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 Vladislava Stojic, Bojana Andjelkovic Cirkovic, Nebojsa Zdravkovic, Jelena Dimitrijevic, Vladan Kocic, Nenad Filipovic, published by University of Kragujevac, Faculty of Medical Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.