The week's pick
Random Articles
Reseach Article
Extended Firefly Prediction Model for Prognosis of Heart Disease
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 25 |
| Year of Publication: 2019 |
| Authors: Jyoti Thakur, Munish Katoch |
10.5120/ijca2019919684
|
Jyoti Thakur, Munish Katoch . Extended Firefly Prediction Model for Prognosis of Heart Disease. International Journal of Computer Applications. 177, 25 ( Dec 2019), 8-12. DOI=10.5120/ijca2019919684
Abstract
In all the diseases, cardiovascular disease or CVD is the main reason for the death all over the world. 1 to 5 in every one thousand persons suffers from the heart disease. Even though advances have been performed to get better surveillance treatment but yet Heart failure diagnosis has been occurred 1.7 years in men and 3.2 years in women. Several techniques have been proposed till now to find the effect of disease at earlier stage but still it is under consideration. Data mining is used for the extraction of significant, meaningful and desired information from the datasets of patients. The different classification algorithms were used in the existing systems for the prediction of heart disease, in which the attributes of data mining are fed. However, it has been analyzed that there is no single classifier that produces best result for dataset and not a single data mining technique that gives consistent results for all types of health related data. Therefore, in this paper, a novel classifier i.e. fa-ANN, is proposed that can provide the optimal results for the healthcare data than other classifiers in terms of accuracy, precision and recall.
References
- Al-Janabi Mahmoud ,H.Qutqut, Mohammad Hijjawi, “Machine learning classification techniques for heart disease prediction: a review”, vol. 7, 2018
- Jabbar MA, “Prediction of heart disease using k-nearest neighbor and particle swarm optimization”, Volume 28, Issue 9,
- Mythili T., et al, “A Heart Disease Prediction Model using SVM-Decision Trees-Logistic Regression (SDL)”, vol. 68, 2013
- .A.Jabbar, “Intelligent heart disease prediction system using random forest and evolutionary approach”, Volume 4 (2016) pp. 175-184
- C. Sowmiya and P. Sumitra, "Analytical study of heart disease diagnosis using classification techniques," 2017, pp. 1-5
- Shafquat Perween , Suraiya Parveen , “Analysis of Heart Disease Prediction Techniques”, Volume 7, Issue 4, April 2018
- H. Chen, et al , "HDPS: Heart disease prediction system," 2011 Computing in Cardiology, Hangzhou, 2011, pp. 557-560
- S. Bharti and S. N. Singh, "Analytical study of heart disease prediction comparing with different algorithms," 2015, pp. 78-82.
- Mamatha Alex P and Shaicy P Shaji, “Prediction and Diagnosis of Heart Disease Patients using Data Mining Technique”, 2019 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2019, pp. 0848-0852.
- AUTHORS PROFILE
- Jyoti Thakur. She received B.Tech degree in Computer Science Engineering from the Sri Sai University Palampur Himachal Pradesh in2017. Currently she is pursuing in M.Tech in Computer Science Engineering from the Sri Sai University Palmpur.
- Munish Katoch. He received his B.Tech degree in Computer Science Engineering from the Lovely Professional University. He also received his M.Tech degree in Computer Science Engineering from Lovely Professional University. Now he is working as Assistant Professor in Sri Sai University Palampur
Index Terms
Keywords