Data Analysis and Predictive Modelling on Heart Disease based on People’s Lifestyle


  • Edward Leonardo Asia Pacific University of Technology & Innovation image/svg+xml
  • Murugananthan Velayutham Asia Pacific University of Technology & Innovation image/svg+xml
  • Justin Gilbert Asia Pacific University of Technology & Innovation image/svg+xml



Coronary Artery Disease, Heart Disease, Machine Learning, Predictive Modelling, Data Analysis


Coronary Artery Disease (CAD) is a form of heart disease primarily influenced by lifestyle choices. Despite preventative measures available to mitigate CAD risks, a significant proportion of the population remains unaware of its severity and consequently neglects necessary precautions. As a result, the influence of CAD continues to rise. This project aims to curb CAD cases by developing an early warning detection and educational accessible to the general population, leveraging Machine Learning and Data Visualization technologies. Research indicates that while Coronary Artery Disease can be mitigated through a lifestyle shift towards healthier living, the risk remains due to factors such as age and natural health deterioration.


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National Cancer Institute, “NCI Dictionary of Cancer Terms | Heart Disease,” National Cancer Institute. (accessed Feb. 08, 2022).

British Heart Foundation, “Global Heart & Circulatory Diseases [Fact sheet],” British Heart Foundation, Feb. 2023. Accessed: Feb. 08, 2023. [Online]. Available:

CDC, “Heart Disease Resources | CDC,” Centers for Disease Control and Prevention, Jul. 12, 2022. (accessed Feb. 08, 2023).

S. Zhou, “Knowing the Importance of Being Healthy in your Early 20s,” Flexispot, Jun. 21, 2021. (accessed Feb. 08, 2023).

Johns Hopkins Medicine, “It’s Never Too Late: Five Healthy Steps at Any Age,” Johns Hopkins Medicine, Nov. 01, 2021. (accessed Feb. 08, 2023).

J. Mock, “Is It Ever Too Late to Start Being Healthy?,” Discover Magazine, Dec. 26, 2019. (accessed Feb. 08, 2023).

IBM, “What is Machine Learning? | IBM,” IBM. (accessed Feb. 08, 2023).

V. Kanade, “What Is Machine Learning? Definition, Types, Applications, and Trends for 2022,” Spiceworks, Aug. 30, 2022. (accessed Feb. 08, 2023).

E. Burns, “Machine Learning,” TechTarget, Mar. 30, 2021. (accessed Feb. 08, 2023).

E. Miah, “Key Factors in The Successful Use of Machine Learning,” Data Science Central, Nov. 07, 2017. (accessed Feb. 08, 2023).

K. Pytlak, “Personal key indicators of heart disease,” Kaggle, Feb. 16, 2022. (accessed Jul. 18, 2023).

Tableau, “What Is Data Visualization? Definition, Examples, And Learning Resources,” Tableau, 2023. (accessed Jul. 11, 2023).

S. Chorev, “A practical guide to data cleaning,” Deepchecks, Mar. 24, 2023.,disappointing%20the%20model%20in%20production. (accessed Jul. 18, 2023).

T. Khan, “Different types of Encoding - AI ML Analytics,” AI ML Analytics, Jan. 02, 2022. (accessed Jul. 15, 2023).

Simplilearn, “What is a Confusion Matrix in Machine Learning?,”, Feb. 2023, [Online]. Available:,actual%20values%20of%20a%20classifier.

B. Harikrishnan, “Confusion matrix, accuracy, precision, recall, F1 score,” Medium, Dec. 12, 2021. Accessed: Jul. 18, 2023. [Online]. Available:




How to Cite

Leonardo E, Velayutham M, Gilbert J. Data Analysis and Predictive Modelling on Heart Disease based on People’s Lifestyle. EAI Endorsed Trans Perv Health Tech [Internet]. 2024 Jun. 26 [cited 2024 Jul. 13];10. Available from: