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An Application of Association Rule Mining to Extract Risk Pattern for Type 2 Diabetes Using Tehran Lipid and Glucose Study Database

Ramezankhani, A., Pournik, O., Shahrabi, J., Azizi, F., & Hadaegh, F. (2015) · Intern J Endocrinol Metab · doi:10.5812/ijem.25389 · Cited by 41 · see citing works

Multilayer perceptron based deep neural network for early detection of coronary heart disease

Masih, N., Naz, H. U., & Ahuja, S. (2020) · Health and Technology · doi:10.1007/s12553-020-00509-3 · Cited by 41 · see citing works

Using Decision Trees in Data Mining for Predicting Factors Influencing of Heart Disease

Abdar, M. (2015) · Carpathian Journal of Electronic and Computer Engineering · Cited by 41 · see citing works

A novel hybrid random forest linear model approach for forecasting groundwater fluoride contamination

Nafouanti, M. B., Li, J., Nyakilla, E. E., Mwakipunda, G. C., & Mulashani, A. K. (2023) · Environmental Science and Pollution Research · doi:10.1007/s11356-023-25886-w · Cited by 39 · see citing works

Diabetic foot ulcers risk prediction in patients with type 2 diabetes using classifier based on associations rule mining

Piran, N., Farhadian, M., Soltanian, A. R., & Borzouei, S. (2024) · Scientific Reports · doi:10.1038/s41598-023-47576-w · Cited by 38 · see citing works

Cardiac ScoreCard: A diagnostic multivariate index assay system for predicting a spectrum of cardiovascular disease

McRae, M. P., Bozkurt, B., Ballantyne, C. M., Sanchez, X., Christodoulides, N. J., Simmons, G. W., Nambi, V., Misra, A., Miller, C. S., Ebersole, J. L., et al. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.01.029 · Cited by 38 · see citing works

An intelligent noninvasive model for coronary artery disease detection

Verma, L., Srivastava, S., & Negi, P. C. (2017) · Complex & Intelligent Systems · doi:10.1007/s40747-017-0048-6 · Cited by 38 · see citing works

Discovering dynamic adverse behavior of policyholders in the life insurance industry

Islam, M. R., Liu, S., Biddle, R., Razzak, I., Wang, X., Tilocca, P., & Xu, G. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120486 · Cited by 38 · see citing works

Risk assessment of inland waterborne transportation using data mining

Wang, Z., & Yin, J. (2020) · Maritime Policy & Management · doi:10.1080/03088839.2020.1738582 · Cited by 37 · see citing works

A new approach to segmenting multichannel shoppers in Korea and the U.S.

Park, J., & Kim, R. B. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2018.09.007 · Cited by 36 · see citing works

Real-time monitoring system for early prediction of heart disease using Internet of Things

Basheer, S., Alluhaidan, A. S., & Bivi, M. A. (2021) · Soft Computing · doi:10.1007/s00500-021-05865-4 · Cited by 36 · see citing works

Highlighting the rules between diagnosis types and laboratory diagnostic tests for patients of an emergency department: Use of association rule mining

Sarıyer, G., & Taşar, C. Ö. (2019) · Health Informatics Journal · doi:10.1177/1460458219871135 · Cited by 35 · see citing works

Diagnosis of Cardiovascular Diseases with Bayesian Classifiers

Fakhr, M. A., & Elsayad, A. M. (2015) · Journal of Computer Science · doi:10.3844/jcssp.2015.274.282 · Cited by 34 · see citing works

Mining frequent patterns and association rules using similarities

Rodríguez‐González, A. Y., Martínez-Trinidad, J. F., Carrasco-Ochoa, J. A., & Ruíz-Shulcloper, J. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.06.041 · Cited by 32 · see citing works

Predicting Heart Disease Based on Influential Features with Machine Learning

Dubey, A. K., Choudhary, K., & Sharma, R. (2021) · Intelligent Automation & Soft Computing · doi:10.32604/iasc.2021.018382 · Cited by 35 · see citing works

Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks

Li, W., Zuo, M., Zhao, H., Xu, Q., & Chen, D. (2021) · Methods · doi:10.1016/j.ymeth.2021.12.009 · Cited by 32 · see citing works

Discovering association rules from big graphs

Fan, W., Fu, W., Jin, R., Lü, P., & Tian, C. (2022) · Proceedings of the VLDB Endowment · doi:10.14778/3523210.3523224 · Cited by 32 · see citing works

Efficient mining of class association rules with the itemset constraint

Nguyen, D., Nguyen, L. T. T., Vo, B., & Pedrycz, W. (2016) · Knowledge-Based Systems · doi:10.1016/j.knosys.2016.03.025 · Cited by 31 · see citing works

Applications of machine learning in animal and veterinary public health surveillance

Guitián, J., Snary, E., ARNOLD, M., & Chang, Y. (2023) · Scientific and Technical Review (World Organisation for Animal Health) · doi:10.20506/rst.42.3366 · Cited by 36 · see citing works

An integrated method of associative classification and neuro-fuzzy approach for effective mammographic classification

Abubacker, N. F., Azman, A., Doraisamy, S. C., & Murad, M. A. A. (2016) · Neural Computing and Applications · doi:10.1007/s00521-016-2290-z · Cited by 29 · see citing works

A survey on data mining techniques used in medicine

Birjandi, S. M., & Khasteh, S. H. (2021) · Journal of Diabetes & Metabolic Disorders · doi:10.1007/s40200-021-00884-2 · Cited by 29 · see citing works

Supervised Machine Learning-Based Cardiovascular Disease Analysis and Prediction

Hossen, M. D. A., Tazin, T., Khan, S., Alam, E., Sojib, H. A., Khan, M. M., & Alsufyani, A. (2021) · Mathematical Problems in Engineering · doi:10.1155/2021/1792201 · Cited by 33 · see citing works

A Hybrid Framework for Heart Disease Prediction Using Machine Learning Algorithms

Chandrika, L., & Madhavi, K. (2021) · E3S Web of Conferences · doi:10.1051/e3sconf/202130901043 · Cited by 28 · see citing works

Performance evaluation of optimal ensemble learning approaches with PCA and LDA-based feature extraction for heart disease prediction

Rabbi, M. S. H., Bari, M. M., Debnath, T., Rahman, A., Das, A. K., Hossain, M. P., & Muhammad, G. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107138 · Cited by 28 · see citing works

An Improved Auto Categorical PSO with ML for Heart Disease Prediction

Dubey, A. K., Sinhal, A. K., & Sharma, R. (2022) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.4854 · Cited by 28 · see citing works

Detecting Lifestyle Risk Factors for Chronic Kidney Disease With Comorbidities: Association Rule Mining Analysis of Web-Based Survey Data

Peng, S., Shen, F., Wen, A., Wang, L., Fan, Y., Liu, X., & Liu, H. (2019) · Journal of Medical Internet Research · doi:10.2196/14204 · Cited by 27 · see citing works

Comorbidity Patterns of Older Lung Cancer Patients in Northeast China: An Association Rules Analysis Based on Electronic Medical Records

Feng, J. Y., Mu, X., Ma, L., & Wang, W. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17239119 · Cited by 27 · see citing works

Artificial Intelligence–Enabled Evaluation of Pain Sketches to Predict Outcomes in Headache Surgery

Chartier, C., Gfrerer, L., Knoedler, L., & Austen, W. G. (2022) · Plastic & Reconstructive Surgery · doi:10.1097/prs.0000000000009855 · Cited by 27 · see citing works

A Weighted Average Ensemble Technique to Predict Heart Disease

Neloy, M. A. I., Nahar, N., Hossain, M. S., & Andersson, K. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-16-7597-3_2 · Cited by 26 · see citing works

Summarization and sentiment analysis from user health posts

Mane, V. L., Panicker, S., & Patil, V. B. (2015) · doi:10.1109/pervasive.2015.7087087 · Cited by 25 · see citing works

A Survey on Breast Cancer Scenario and Prediction Strategy

Dubey, A. K., Gupta, U. C., & Jain, S. A. (2014) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-11933-5_40 · Cited by 25 · see citing works

Artificial Intelligence and Data Mining Methods for Cardiovascular Risk Prediction

Georga, E. I., Tachos, N. S., Sakellarios, A. I., Kigka, V. I., Exarchos, T. P., Pelosi, G., Parodi, O., Michalis, L. K., & Fotiadis, D. I. (2019) · Series in bioengineering · doi:10.1007/978-981-10-5092-3_14 · Cited by 25 · see citing works

Mental disorders and medical comorbidities: Association rule mining approach

Wang, C., Lee, T.-Y., Hui, K.-C., & Chung, M. (2019) · Perspectives In Psychiatric Care · doi:10.1111/ppc.12362 · Cited by 25 · see citing works

On the Problems of Knowledge Acquisition and Representation of Expert System for Diagnosis of Coronary Artery Disease (CAD)

Muhammad, L. J., Garba, E. J., Oye, N. D., & Wajiga, G. M. (2018) · International Journal of u- and e- Service Science and Technology · doi:10.14257/ijunesst.2018.11.3.05 · Cited by 24 · see citing works

Feature Selection in Pre-Diagnosis Heart Coronary Artery Disease Detection: A heuristic approach for feature selection based on Information Gain Ratio and Gini Index

Ghasemi, F., Neysiani, B. S., & Nematbakhsh, N. (2020) · International Conference on Web Research (ICWR) · doi:10.1109/icwr49608.2020.9122285 · Cited by 24 · see citing works

Mine-first association rule mining: An integration of independent frequent patterns in distributed environments

Mudumba, B., & Kabir, M. F. (2024) · Decision Analytics Journal · doi:10.1016/j.dajour.2024.100434 · Cited by 24 · see citing works

Developing an expert prognosis system of the reciprocating compressor based on associations among monitoring parameters and maintenance records

Lu, Y., Tung, F.-Y., & Wang, C. (2020) · Journal of Loss Prevention in the Process Industries · doi:10.1016/j.jlp.2020.104382 · Cited by 23 · see citing works

Heart Disorders Forecasting with Feature Engineering using Non-Parametric Classifier

Bhatt, T., Tripathi, V., Mishra, S., Alkhayyat, A. H., & Mishra, N. (2024) · International Conference on Intelligent Computing and Emerging Communication Technologies (ICEC) · doi:10.1109/icec59683.2024.10837504 · Cited by 22 · see citing works

Discovering diverse association rules from multidimensional schema

Usman, M., Pears, R., & Fong, A. C. M. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.05.031 · Cited by 22 · see citing works

What are the occupational hazards of construction project managers: A data mining analysis in China

Li, X., Fei, Y., Rizzuto, T. E., & Yang, F. (2020) · Safety Science · doi:10.1016/j.ssci.2020.105088 · Cited by 22 · see citing works

An Effective Classification Algorithm for Heart Disease Prediction with Genetic Algorithm for Feature Selection

Kanwal, S., Rashid, J., Nisar, M. W., Kim, J., & Hussain, A. (2021) · Mohammad Ali Jinnah University International Conference on Computing (MAJICC) · doi:10.1109/majicc53071.2021.9526242 · Cited by 22 · see citing works

TWO PHASE PARALLEL FRAMEWORK FOR WEIGHTED COALESCE RULE MINING: A FAST HEART DISEASE AND BREAST CANCER PREDICTION PARADIGM

Moturi, S., Vemuru, S., & Rao, S. N. T. (2022) · Biomedical Engineering Applications Basis and Communications · doi:10.4015/s1016237222500107 · Cited by 22 · see citing works

Heart Disease Prediction Using Machine Learning Algorithms with Self-Measurable Physical Condition Indicators

Sun, H., & Pan, J. (2023) · Journal of Data Analysis and Information Processing · doi:10.4236/jdaip.2023.111001 · Cited by 22 · see citing works

A Parallel MapReduce Algorithm to Efficiently Support Itemset Mining on High Dimensional Data

Apiletti, D., Baralis, E., Cerquitelli, T., Garza, P., Pulvirenti, F., & Pietro Michiardi, A. (2017) · Big Data Research · doi:10.1016/j.bdr.2017.10.004 · Cited by 22 · see citing works

Profile-based assessment of diseases affective factors using fuzzy association rule mining approach: A case study in heart diseases

Yavari, A., Rajabzadeh, A., & Abdali-Mohammadi, F. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103695 · Cited by 22 · see citing works

Prediction of Diabetes Using Internet of Things (IoT) and Decision Trees: SLDPS

Allugunti, V. R., Reddy, C. K. K., Elango, N. M., & Anisha, P. R. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-981-15-5679-1_43 · Cited by 21 · see citing works

The relationship between the healthy eating index and an alternate healthy eating index with the risk factors for cardiovascular disease in a population from northeastern Iran

Khakpouri, S., Safari, M., Ghazizadeh, H., Parizadeh, S. M. R., Nematy, M., Tayefi, M., Ferns, G. A., Saberi‐Karimian, M., & Ghayour‐Mobarhan, M. (2019) · Translational Metabolic Syndrome Research · doi:10.1016/j.tmsr.2019.05.001 · Cited by 22 · see citing works

A STUDY ON ASSOCIATION RULE MINING FOR VARIOUS HEART DISEASES MEDICAL DATA

Choudhary, A. K. (2019) · International journal of advance research and innovative ideas in education

Detection of Heart Disease Using Association Pattern Mining

Islam, A. T., Hasan, M. R., Hasan, S., & Yasmeen, F. (2023) · IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE) · doi:10.1109/wiecon-ece60392.2023.10456373 · Cited by 2 · see citing works

Diagnosis heart disease using an association rule discovery approach

Nahar, J., (9776756), A. B. M. S. A., Tickle, K. S., & (7800338), Y. C. (2009) · Acquire (CQUniversity)

Heart Disease Predictive Analysis Using Association Rule Mining

Inamdar, F. D. M. A. F. M., Jayakumar, N., & Bari, B. (2022) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-19-1844-5_10 · Cited by 4 · see citing works

Study of Factors for Heart Disease Prediction between Men and Women based on Multiple Regression Models

Guo, J. (2023) · Highlights in Science Engineering and Technology · doi:10.54097/hset.v54i.9755