Optimized Classification of Cardiovascular Disease Using Machine Learning Paradigms
DOI:
https://doi.org/10.21015/vtse.v11i2.1527Abstract
Nearly 19 million people die each year from cardiovascular and chronic respiratory diseases, which are a global threat. It is necessary to address the causes of these diseases because of the high death rate. The investigation uncovered a number of causes, but the inability to forecast these diseases symptoms is by far the most significant. In this work, we developed a method for anticipating these diseases crucial symptoms, which will aid in early disease diagnosis and allow patients to begin treatment. This research will introduce a new computational medicine research using machine learning (ML) paradigms to forecast cardiovascular disease (CVD). Data were processed by methods in sequence with various parameters. different models created that predicts CVD risk based on individual age, gender, ethnicity, body mass etc., and lifestyle factors. The research will also focus on performing complete comparison of ML models. We will apply Five ML based algorithems such as Decision Tree (DT), K-Nearest Neighbors (KNN), Naïve Bayes (NB), XGBOOST and Random Forest and evaluate these models on the basis of Training and Testing and also calculated the Presicion Recall and F1-Score for each model. Naïve Bayes and XGBOOST Classifier perform better with accuracy of 92.31 and 92.34 percent as compared to other models.
References
. K. Reynolds, A. S. Go, T. K. Leong, D. M. Boudreau, A. E. Cassidy-Bushrow, S. P. Fortmann, et al., "Trends in incidence of hospitalized acute myocardial infarction in the Cardiovascular Research Network (CVRN)," The American Journal of Medicine, vol. 130, no. 3, pp. 317-327, 2017.
. U. Nagavelli, D. Samanta, and P. Chakraborty, "Machine Learning Technology-Based Heart Disease Detection Models," Journal of Healthcare Engineering, vol. 2022, pp. 1-9, 2022. doi: 10.1155/2022/7351061.
. B. Troesch, H. K. Biesalski, R. Bos, E. Buskens, P. C. Calder, W. H. Saris, et al., "Increased intake of foods with high nutrient density can help to break the intergenerational cycle of malnutrition and obesity," Nutrients, vol. 7, no. 7, pp. 6016-6037, 2015.
. S. Nashif, M. R. Raihan, M. R. Islam, and M. H. Imam, "Heart disease detection by using machine learning algorithms and a real-time cardiovascular health monitoring system," World Journal of Engineering and Technology, vol. 6, no. 4, pp. 854-873, 2018.
. L. C. Mantoani, S. Dell'Era, W. MacNee, and R. A. Rabinovich, "Physical activity in patients with COPD: the impact of comorbidities," Expert Review of Respiratory Medicine, vol. 11, no. 9, pp. 685-698, 2017.
. M. Heron, "Deaths: Leading causes for (2010)," Natl. Vital Stat. Reports, vol. 62, no. 6.
. R. J. P. Princy, S. Parthasarathy, P. S. Hency Jose, A. Raj Lakshminarayanan, and S. Jeganathan, "Prediction of Cardiac Disease using Supervised Machine Learning Algorithms," 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), 2020, pp. 570-575, doi: 10.1109/ICICCS48265.2020.9121169.
. J. M. Fermont, M. Fisk, C. E. Bolton, W. MacNee, J. R. Cockcroft, J. Fuld, et al., "Cardiovascular risk prediction using physical performance measures in COPD: results from a multicentre observational study," BMJ Open, vol. 10, no. 12, p. e038360, 2020.
. A. Shaikh Abdul Hannan, A. V. Mane, R. R. Manza, and R. J. Ramteke, "Prediction of Heart Disease Medical Prescription using Radial Basis Function," IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Dec. 2010, pp. 28-29, doi: 10.1109/ICCIC.2010.5705900.
. M. Shouman, T. Turner, and R. Stocker, "Applying k-Nearest Neighbors in Diagnosing Heart Disease Patients," International Journal of Information and Education Technology, vol. 2, no. 3, pp. 220-223, Jun. 2012.
. J. Patel, T. Upadhyay, and S. Patel, "Heart Disease Prediction using Machine Learning and Data Mining Technique," vol. 7, no. 1, pp. 129-137, Sep. 2015-Mar. 2016.
. A. Jagtap, P. Malewadkar, O. Baswat, and H. Rambade, "Heart disease prediction using machine learning," International Journal of Research in Engineering, Science and Management, vol. 2, no. 2, pp. 352-355, 2019.
. W. A. A. Wghmode, D. Sawant, and D. D. Ketkar, "Heart Disease Prediction Using Data Mining Techniques," Heart Disease, 2017.
. M. Anbarasi, E. Anupriya, and N. C. S. N. Iyengar, "Enhanced prediction of heart disease with feature subset selection using genetic algorithm," International Journal of Engineering Science and Technology, vol. 2, no. 10, pp. 5370-5376, 2010.
. E. Taylor, P. S. Ezekiel, and F. B. Deedam-Okuchaba, "A Model to Detect Heart Disease using Machine Learning Algorithm," International Journal of Computer Sciences and Engineering, 2019.
. M. Singh, L. M. Martins, P. Joanis, and V. K. Mago, "Building a Cardiovascular Disease Predictive Model using Structural Equation Model & Fuzzy Cognitive Map," IEEE International Conference on Fuzzy Systems (FUZZ), 2016, pp. 1377-1382.
. M. Gudadhe, K. Wankhade, and S. Dongre, "Decision Support System for Heart Disease Based on Support Vector Machine and Artificial Neural Network," International Conference on Computer and Communication Technology (ICCCT), Sept. 2010, pp. 17-19, doi: 10.1109/ICCCT.2010.5640377.
. M. L. Sharan and B. S. Kumar, "Analysis of Cardiovascular Heart Disease Prediction Using Data Mining Techniques," International Journal of Modern Computer Science, vol. 4, no. 1, pp. 55-58, Feb. 2016.
. D. S. Medhekar, M. P. Bote, and S. D. Deshmukh, "Heart Disease Prediction System Using Naive Bayes," International Journal of Enhanced Research in Science Technology & Engineering, vol. 2, no. 3, pp. 1-5, Mar. 2013.
. N. Ajam, "Heart Diseases Diagnoses Using Artificial Neural Network," Network And Complex Systems, vol. 5, no. 4, pp. 7-11, Feb. 2015. ISSN: 2224-610X (Paper), ISSN: 2225-0603 (Online).
. B. Bahrami and M. H. Shirvani, "Prediction and Diagnosis of Heart Disease by Data Mining Techniques," Journal of Multidisciplinary Engineering Science and Technology (JMEST), vol. 2, no. 2, pp. 164-168, Feb. 2015. ISSN: 3159-0040.
. M. S. Maqbool, I. Hanif, S. Iqbal, A. Basit, and A. Shabbir, "Optimized Feature Extraction and Cross-Lingual Text Reuse Detection using Ensemble Machine Learning Models," Journal of Computing & Biomedical Informatics, vol. 5, no. 01, pp. 26-40, 2023.
. U. Fazal, M. Khan, M. S. Maqbool, H. Bibi, and R. Nazeer, "Sentiment Analysis of Omicron Tweets by using Machine Learning Models," Journal of Computing & Biomedical Informatics, 5(01), pp. 82-95, 2023.
. M. A. Hasnain, S. Ali, H. Malik, M. Irfan, and M. S. Maqbool, "Deep Learning-Based Classification of Dental Disease Using X-Rays," Journal of Computing & Biomedical Informatics, vol. 5, no. 01, pp. 82-95, 2023.
. A. Basit, I. Hanif, M. S. Maqbool, W. Qayyum, M. A. Hasnain, and R. Nazeer, "Cross-Lingual Information Retrieval in a Hybrid Query Model for Optimality," Journal of Computing & Biomedical Informatics, vol. 5, no. 01, pp. 130-141, 2023.
. V. Shorewala, "Early detection of coronary heart disease using ensemble techniques," Informatics Med. Unlocked, vol. 26, p. 100655, Jan. 2021, doi: 10.1016/J.IMU.2021.100655.
. I. Gupta, R. Shangle, V. Latiyan, and U. Soni, "Cardiovascular Disease Detection using Artificial Immune System and other Machine Learning Models," J. Phys. Conf. Ser., vol. 1950, no. 1, p. 012032, Aug. 2021, doi: 10.1088/1742-6596/1950/1/012032.
. M. I. H. Khan and M. R. H. Mondal, "Data-Driven Diagnosis of Heart Disease," Int. J. Comput. Appl., vol. 176, no. 41, pp. 46-54, Jul. 2020, doi: 10.5120/IJCA2020920549.
. S. Palaniappan and R. Awang, "Intelligent heart disease prediction system using data mining techniques," in 2008 IEEE/ACS International Conference on Computer Systems and Applications, 2008, pp. 108-115.
. A. Taneja, "Heart disease prediction system using data mining techniques," Oriental Journal of Computer Science and Technology, vol. 6, no. 4, pp. 457-466, 2013.
. S. Anitha and N. Sridevi, "Heart disease prediction using data mining techniques," Journal of Analysis and Computation, vol. 6, no. 4, pp. 457-466, 2019.
. C. S. M. Wu, M. Badshah, and V. Bhagwat, "Heart disease prediction using data mining techniques," in Proceedings of the 2019 2nd International Conference on Data Science and Information Technology, 2019, pp. 7-11.
. C. Krittanawong, H. Zhang, Z. Wang, M. Aydar, and T. Kitai, "Artificial intelligence in precision cardiovascular medicine," Journal of the American College of Cardiology, vol. 69, no. 21, pp. 2657-2664, 2017.
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