Cardiovascular disease detection from high utility rare rule mining-Reference-Cited by-同舟云学术

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Cardiovascular disease detection from high utility rare rule mining

Published:2022-09 Issue: Volume:131 Page:102347
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Iqbal Mohammad,Setiawan Muhammad Nanda,Irawan Mohammad Isa,Khalif Ku Muhammad Naim Ku,Muhammad Noryanti,Aziz Mohd Khairul Bazli Mohd

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference36 articles.

1. Cardiovascular disease risk factor prevalence and estimated 10-year cardiovascular risk scores in Indonesia: the SMARThealth Extend study;Maharani;PLoS One,2019

2. Global progress in prevention of cardiovascular disease;Mendis;Cardiovasc Diagn Ther,2017

3. Extracting production rules for cerebrovascular examination dataset through mining of non-anomalous association rules;Ou-Yang;Appl Sci,2019

4. Identifying risk factors for adverse diseases using dynamic rare association rule mining;Borah;Expert Syst Appl,2018

5. Identification of significant features and data mining techniques in predicting heart disease;Amin;Telemat Informa,2019

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3. SPM4GAC: SPM based approach for genome analysis and classification of macromolecules;International Journal of Biological Macromolecules;2024-05

4. An efficient cardio vascular disease prediction using multi-scale weighted feature fusion-based convolutional neural network with residual gated recurrent unit;Computer Methods in Biomechanics and Biomedical Engineering;2024-04-17

5. TKU-PSO: An Efficient Particle Swarm Optimization Model for Top-K High-Utility Itemset Mining;International Journal of Interactive Multimedia and Artificial Intelligence;2024

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