1
Department of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt
(Abdelaziz A. Abdelhamid)
2
Faculty of Artiļ¬cial Intelligence, Delta University for Science and Technology, Mansoura 11152, Egypt
(mmm@ieee.org)
3
Department of System Programming, South Ural State University, 454080 Chelyabinsk, Russia
(abotalebmostafa@bk.ru)
4
Computer Science and Intelligent Systems Research Center, Blacksburg 24060, Virginia, USA
(sktowfek@jcsis.org)
Abstract :
Diabetes patients face a severe health cost from cardiovascular disease (CVD). Recognising the risk factors for CVD in this group of people is critical for developing effective preventative and management measures. In this study, we use an ontological data mining approach, LightGBM, to analyze a dataset of diabetes patients and investigate the risk variables that contribute to CVD. The association between diabetes and CVD is investigated, emphasising the increased risk that diabetes patients confront. We look into the demographics, health behaviors, and physiological indicators that influence the emergence of heart disease in this population. We use LightGBM to find complicated relationships and trends within the dataset, allowing us to identify critical risk variables. Our research contributes to the field by offering a thorough examination of the diabetes-CVD link and applying an advanced machine-learning technique for information extraction. The results have implications for specific interventions, risk evaluation models, and personalised therapy approaches aimed at reducing the effect of CVD in diabetics.
Keywords :
Cardiovascular disease; Diabetes , Risk causes; Ontological data mining; Knowledge representation; Data-driven techniques; Semantic reasoning; Health data analysis.
References :
[1] Qrenawi M I, Al Sarraj W, Identification of cardiovascular diseases risk factors among diabetes patients using ontological data mining techniques. In 2018 International Conference on Promising Electronic Technologies (ICPET), 129-134, 2018.
[2] M. Saber, Efficient phase recovery system, Indonesian Journal of Electrical Engineering and Computer Science (lJEECS), 5(1), 123-129, 2017.
[3] Mahmoud H, Abbas E, Fathy I, Data mining and ontology-based techniques in healthcare management. International Journal of Intelligent Engineering Informatics, 6(6), 509-526, 2018.
[4] Kavakiotis I, Tsave O, Salifoglou A, Maglaveras N, Vlahavas I, Chouvarda I, Machine learning and data mining methods in diabetes research. Computational and structural biotechnology journal, 15, 104-116, 2017.
[5] Mehmood A, Iqbal M, Mehmood Z, Irtaza A, Nawaz M, Nazir T, Masood M, Prediction of heart disease using deep convolutional neural networks. Arabian Journal for Science and Engineering, 46(4), 3409-3422, 2021.
[6] Mohamed Saber, A novel design and Implementation of FBMC transceiver for low power applications, Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 8(1), 83-93, 2020.
[7] Tiwari P, Singh V, Diabetes disease prediction using significant attribute selection and classification approach. In Journal of Physics: Conference Series, 1714(1), p. 012013, 2021.
[8] Eid Marwa M, Fawaz Alassery, Abdelhameed Ibrahim, and Mohamed Saber, Metaheuristic optimization algorithm for signals classification of electroencephalography channels. Computers, Materials & Continua, 71(3), 4627-4641, 2022.
[9] Alharbi AH et al., Diagnosis of Monkeypox Disease Using Transfer Learning and Binary Advanced Dipper Throated Optimization Algorithm. Biomimetics, 8(3),313, 2023.
[10] Ali F, El-Sappagh S, Islam S R, Kwak D, Ali A, Imran M, Kwak, K S, A smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion. Information Fusion, 63, 208-222, 2020.
[11] M. M. E. Bahy, S. A. Ward, M. Badawi and R. Morsi, "Particle-initiated negative corona in co-axial cylindrical configuration. Annual Report Conference on Electrical Insulation and Dielectric Phenomena, Montreal, QC, Canada, 343-348, 2012.
[12] E. M. Shaalan, S. M. Ghania and S. A. Ward, Analysis of electric field inside HV substations using charge simulation method in three dimensional. Annual Report Conference on Electrical Insulation and Dielectic Phenomena, West Lafayette, IN, USA,1-5, 2010.
[13] Mohamed A. Abouelatta, et al. , Measurement and assessment of corona current density for HVDC bundle conductors by FDM integrated with full multigrid technique. Electric Power Systems Research, 199, 2021.
[14] Amin Samy, Sayed A. Ward, Mahmud N Ali, Conventional Ratio and Artificial Intelligence (AI) Diagnostic methods for DGA in Electrical Transformers. International Electruical Engineering Journal, 6, 2096-2102, 2015.
[15] El-Kenawy, El-Sayed M., Marwa Eid, and Alshimaa H. Ismail, A New Model for Measuring Customer Utility Trust in Online Auctions. International Journal of Computer Applications, 975, 8887, 2020.
| Style | # |
|---|---|
| MLA | Abdelaziz A. Abdelhamid, Marwa M. Eid, Mostafa Abotaleb, S. K. Towfek. "Identification of Cardiovascular Disease Risk Factors Among Diabetes Patients using ontological Data Mining Techniques." Journal of Artificial Intelligence and Metaheuristics, Vol. 4, No. 2, 2023 ,PP. 45-53 (Doi : https://doi.org/10.54216/JAIM.040205) |
| APA | Abdelaziz A. Abdelhamid, Marwa M. Eid, Mostafa Abotaleb, S. K. Towfek. (2023). Identification of Cardiovascular Disease Risk Factors Among Diabetes Patients using ontological Data Mining Techniques. Journal of Journal of Artificial Intelligence and Metaheuristics, 4 ( 2 ), 45-53 (Doi : https://doi.org/10.54216/JAIM.040205) |
| Chicago | Abdelaziz A. Abdelhamid, Marwa M. Eid, Mostafa Abotaleb, S. K. Towfek. "Identification of Cardiovascular Disease Risk Factors Among Diabetes Patients using ontological Data Mining Techniques." Journal of Journal of Artificial Intelligence and Metaheuristics, 4 no. 2 (2023): 45-53 (Doi : https://doi.org/10.54216/JAIM.040205) |
| Harvard | Abdelaziz A. Abdelhamid, Marwa M. Eid, Mostafa Abotaleb, S. K. Towfek. (2023). Identification of Cardiovascular Disease Risk Factors Among Diabetes Patients using ontological Data Mining Techniques. Journal of Journal of Artificial Intelligence and Metaheuristics, 4 ( 2 ), 45-53 (Doi : https://doi.org/10.54216/JAIM.040205) |
| Vancouver | Abdelaziz A. Abdelhamid, Marwa M. Eid, Mostafa Abotaleb, S. K. Towfek. Identification of Cardiovascular Disease Risk Factors Among Diabetes Patients using ontological Data Mining Techniques. Journal of Journal of Artificial Intelligence and Metaheuristics, (2023); 4 ( 2 ): 45-53 (Doi : https://doi.org/10.54216/JAIM.040205) |
| IEEE | Abdelaziz A. Abdelhamid, Marwa M. Eid, Mostafa Abotaleb, S. K. Towfek, Identification of Cardiovascular Disease Risk Factors Among Diabetes Patients using ontological Data Mining Techniques, Journal of Journal of Artificial Intelligence and Metaheuristics, Vol. 4 , No. 2 , (2023) : 45-53 (Doi : https://doi.org/10.54216/JAIM.040205) |