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Submitted
Jun 23, 2024
Accepted
Jan 31, 2025
Published
Jan 31, 2025
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Abstract

Heart is a very important part of human body, it supply blood to body. If the heart fail down the person
cannot survive. This is very important to diagnose the heart disease timely to start proper treatment.
To dingoes this disease manually takes time a lot and budget of the patient. Traditionally the patient
have to go through form different test then he have to give medical history to the doctor then the doctor
make decision about their disease and then the treatment start. In the developing countries especially
like Pakistan the income of the people are too much low and they cannot offered different type of
expensive tests like ECG etc. In this way the disease cannot detect timely and cannot treated properly.
The heart stroke can be predicted by analyzing different attributes like blood pressure, cholesterol age
etc., this is a best and easy way to predict heat stroke timely. Different types of Machine Learning and
deep learning algorithms are used for heart stroke predictions. In this paper we purposed Novel Multi
Layer-Perceptron (MLP) that are efficient in classification and in heart stoke prediction that model
achieve high accuracy of 99%.

Keywords

Heart disease detection cardiovascular disease Classification algorithms medical imaging

Article Details

Lisensi Creative Commons
This work is licensed under a Lisensi Creative Commons Atribusi-BerbagiSerupa 4.0 Internasional.

How to Cite
[1]
M. Zaman, “A Novel Multi-Level Perceptron for Accurate Heart Stroke Diagnosis”, bit-cs, vol. 6, no. 1, pp. 46-55, Jan. 2025.

References

  1. Heidenreich, P. A., et al. (2011). "Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association." Circulation 123(8): 933-944.
  2. Conrad, N., et al. (2018). "Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals." The Lancet 391(10120): 572-580.
  3. López-Sendón, J. (2011). "The heart failure epidemic." Medicographia 33(4): 363-369.
  4. Allen, L. A., et al. (2012). "Decision making in advanced heart failure: a scientific statement from the American Heart Association." Circulation 125(15): 1928-1952.
  5. Ghwanmeh, S., et al. (2013). Innovative artificial neural networks-based decision support system for heart diseases diagnosis.
  6. Al-Shayea, Q. K. (2011). "Artificial neural networks in medical diagnosis." International Journal of Computer Science Issues 8(2): 150-154
  7. Gavhane, A., et al. (2018). Prediction of heart disease using machine learning. 2018 second international conference on electronics, communication and aerospace technology (ICECA), IEEE.
  8. Chen, K., et al. (2018). Heart murmurs clustering using machine learning. 2018 14th IEEE International Conference on Signal Processing (ICSP), IEEE.
  9. Islam, A. M. and A. Majumder (2013). "Coronary artery disease in Bangladesh: A review." Indian heart journal 65(4): 424-435.
  10. Melnyk, J., et al. (2015). "Awareness and knowledge of cardiovascular risk through blood pressure and cholesterol testing in college freshmen." American Journal of Health Education 46(3): 138-143.
  11. Nahar, J., et al. (2013). "Computational intelligence for heart disease diagnosis: A medical knowledge driven approach." Expert systems with applications 40(1): 96-104.
  12. Sree, S. V., et al. (2012). "Cardiac arrhythmia diagnosis by HRV signal processing using principal component analysis." Journal of Mechanics in Medicine and Biology 12(05): 1240032.
  13. Liu, N., et al. (2012). "An intelligent scoring system and its application to cardiac arrest prediction." IEEE Transactions on Information Technology in Biomedicine 16(6): 1324-1331.
  14. Exarchos, K. P., et al. (2014). "A multiscale approach for modeling atherosclerosis progression." IEEE journal of biomedical and health informatics 19(2): 709-719.
  15. Wiharto, W., et al. (2016). "Intelligence system for diagnosis level of coronary heart disease with K-star algorithm." Healthcare informatics research 22(1): 30.
  16. Saboor, A., et al. (2022). "A method for improving prediction of human heart disease using machine learning algorithms." Mobile Information Systems 2022(1): 1410169.
  17. Ahmad, G. N., et al. (2022). "Efficient medical diagnosis of human heart diseases using machine learning techniques with and without GridSearchCV." IEEE Access 10: 80151-80173.
  18. Ahmad, G. N., et al. (2022). "Comparative study of optimum medical diagnosis of human heart disease using machine learning technique with and without sequential feature selection." IEEE Access 10: 23808-23828.
  19. Suresh, T., et al. (2022). "A hybrid approach to medical decision-making: diagnosis of heart disease with machine-learning model." International Journal of Electrical and Computer Engineering (IJECE) 12(2): 1831-1838.
  20. Pal, M., et al. (2022). "Risk prediction of cardiovascular disease using machine learning classifiers." Open Medicine 17(1): 1100-1113.
  21. Ansarullah, S. I., et al. (2022). "Significance of Visible Non‐Invasive Risk Attributes for the Initial Prediction of Heart Disease Using Different Machine Learning Techniques." Computational intelligence and neuroscience 2022(1): 9580896.
  22. Hasanova, H., et al. (2022). "A novel blockchain-enabled heart disease prediction mechanism using machine learning." Computers and Electrical Engineering 101: 108086.
  23. El-Hasnony, I. M., et al. (2022). "Multi-label active learning-based machine learning model for heart disease prediction." Sensors 22(3): 1184.
  24. Absar, N., et al. (2022). The efficacy of machine-learning-supported smart system for heart disease prediction. Healthcare, MDPI.
  25. Yilmaz, R. and F. H. YAĞIN (2022). "Early detection of coronary heart disease based on machine learning methods." Medical Records 4(1): 1-6.
  26. Özbilgin, F., et al. (2023). "Prediction of coronary artery disease using machine learning techniques with iris analysis." Diagnostics 13(6): 1081.
  27. Bhatt, C. M., et al. (2023). "Effective heart disease prediction using machine learning techniques." Algorithms 16(2): 88.
  28. Nandy, S., et al. (2023). "An intelligent heart disease prediction system based on swarm-artificial neural network." Neural Computing and Applications 35(20): 14723-14737.
  29. Manimurugan, S., et al. (2022). "Two-stage classification model for the prediction of heart disease using IoMT and artificial intelligence." Sensors 22(2): 476.
  30. MAlnajjar, M. K. and S. S. Abu-Naser (2022). "Heart sounds analysis and classification for cardiovascular diseases diagnosis using deep learning."
  31. Atallah, R. and A. Al-Mousa (2019). Heart disease detection using machine learning majority voting ensemble method. 2019 2nd international conference on new trends in computing sciences (ictcs), IEEE.
  32. Tougui, I., et al. (2020). "Heart disease classification using data mining tools and machine learning techniques." Health and Technology 10(5): 1137-1144.
  33. Pawlovsky, A. P. (2018). An ensemble based on distances for a kNN method for heart disease diagnosis. 2018 international conference on electronics, information, and communication (ICEIC), IEEE.
  34. Kavitha, M., et al. (2021). Heart disease prediction using hybrid machine learning model. 2021 6th international conference on inventive computation technologies (ICICT), IEEE.
  35. Almazroi, A. A., et al. (2023). "A clinical decision support system for heart disease prediction using deep learning." IEEE Access.
  36. Mohan, S., et al. (2019). "Effective heart disease prediction using hybrid machine learning techniques." IEEE Access 7: 81542-81554.
  37. Goyal, S. (2022). Predicting the heart disease using machine learning techniques. ICT Analysis and Applications: Proceedings of ICT4SD 2022, Springer: 191-199.
  38. Bharti, R., et al. (2021). "Prediction of heart disease using a combination of machine learning and deep learning." Computational intelligence and neuroscience 2021(1): 8387680.

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