A smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion

Information Fusion - Tập 63 - Trang 208-222 - 2020
Farman Ali1, Shaker El-Sappagh2,3, S.M. Riazul Islam4, Daehan Kwak5, Amjad Ali6, Muhammad Imran7, Kyung-Sup Kwak8
1Department of Software Sejong University, Seoul South Korea
2Centro Singular de Investigación en Tecnoloxías Intelixentes (CiTIUS), Universidade de Santiago de Compostela, 15782, Santiago de Compostela, Spain
3Information Systems Department, Faculty of Computer and Artificial Intelligence, Benha University, Banha 13518, Egypt
4Department of Computer Science and Engineering, Sejong University, Seoul, South Korea
5Department of Computer Science, Kean University, Union, USA
6Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan
7College of Applied Computer Science, King Saud University, Riyadh, Saudi Arabia
8Department of Information and Communication Engineering, Inha University, Incheon, South Korea

Tài liệu tham khảo

Ahmed, 2019, Heart disease identification from patients’ social posts, machine learning solution on Spark, Futur. Gener. Comput. Syst Al-Hamadani, 2016, An Emergency Unit Support System to Diagnose Chronic Heart Failure Embedded with SWRL and Bayesian Network, Int. J. Adv. Comput. Sci. Appl, 7, 446 Al-Makhadmeh, 2019, Utilizing IoT wearable medical device for heart disease prediction using higher order Boltzmann model: a classification approach, Measurement, 147, 10.1016/j.measurement.2019.07.043 Ali, 2019, Fuzzy ontology and LSTM-based text mining: a transportation network monitoring system for assisting travel, Sensors (Switzerland), 19 Ali, 2017, Type-2 fuzzy ontology-aided recommendation systems for IoT-based healthcare, Comput. Commun Ali, 2015, Type-2 fuzzy ontology-based semantic knowledge for collision avoidance of autonomous underwater vehicles, Inf. Sci. (Ny), 295, 441, 10.1016/j.ins.2014.10.013 Ali, 2015, Type-2 fuzzy ontology-based opinion mining and information extraction: a proposal to automate the hotel reservation system, Appl. Intell, 42, 481, 10.1007/s10489-014-0609-y Ali, 2019, Transportation sentiment analysis using word embedding and ontology-based topic modeling, Knowledge-Based Syst, 10.1016/j.knosys.2019.02.033 Ali, 2017, Fuzzy ontology-based sentiment analysis of transportation and city feature reviews for safe traveling, Transp. Res. Part C Emerg. Technol, 77, 33, 10.1016/j.trc.2017.01.014 Ali, 2016, Opinion mining based on fuzzy domain ontology and Support Vector Machine: a proposal to automate online review classification, Appl. Soft Comput, 47, 235, 10.1016/j.asoc.2016.06.003 Ali, 2016, Opinion mining based on fuzzy domain ontology and Support Vector Machine: a proposal to automate online review classification, Appl. Soft Comput. J, 47, 235, 10.1016/j.asoc.2016.06.003 Ayata, 2018, Emotion Based Music Recommendation System Using Wearable Physiological Sensors, IEEE Trans. Consum. Electron., 64, 196, 10.1109/TCE.2018.2844736 Bernal, 2018, Deep temporal multimodal fusion for medical procedure monitoring using wearable sensors, IEEE Trans. Multimed, 20, 107, 10.1109/TMM.2017.2726187 Bhuvaneswari, 2014, An intelligent approach based on Principal Component Analysis and Adaptive Neuro Fuzzy Inference System for predicting the risk of cardiovascular diseases, 241 Chung, 2019, Sensor data acquisition and multimodal sensor fusion for human activity recognition using deep learning, Sensors (Switzerland), 19 Davoodi, 2018, Mortality prediction in intensive care units (ICUs) using a deep rule-based fuzzy classifier, J. Biomed. Inform., 79, 48, 10.1016/j.jbi.2018.02.008 Din, 2019, Smart health monitoring and management system: toward autonomous wearable sensing for Internet of Things using big data analytics, Futur. Gener. Comput. Syst, 91, 611, 10.1016/j.future.2017.12.059 Fazlic, 2019, A novel NLP-fuzzy system prototype for information extraction from medical guidelines, 1025 Hao, 2019, Recurrent convolutional neural network based multimodal disease risk prediction, Futur. Gener. Comput. Syst., 92, 76, 10.1016/j.future.2018.09.031 Jabeen, 2019, An IoT based efficient hybrid recommender system for cardiovascular disease, Peer-to-Peer Netw. Appl, 12, 1263, 10.1007/s12083-019-00733-3 Jiang, 2019, A Correlation-Based Feature Weighting Filter for Naive Bayes, IEEE Trans. Knowl. Data Eng, 31, 201, 10.1109/TKDE.2018.2836440 Jiang, 2019, Class-specific attribute weighted naive Bayes, Pattern Recognit, 88, 321, 10.1016/j.patcog.2018.11.032 Jonnagaddala, 2015, Coronary artery disease risk assessment from unstructured electronic health records using text mining, J. Biomed. Inform., 58, S203, 10.1016/j.jbi.2015.08.003 Jonnalagadda, 2017, Text Mining of the Electronic Health Record: an Information Extraction Approach for Automated Identification and Subphenotyping of HFpEF Patients for Clinical Trials, J. Cardiovasc. Transl. Res., 10, 313, 10.1007/s12265-017-9752-2 Kabir, 2018, Normalization and weighting techniques based on genuine-impostor score fusion in multi-biometric systems, IEEE Trans. Inf. Forensics Secur, 13, 1989, 10.1109/TIFS.2018.2807790 Kamarudin, 2017, A LogitBoost-Based Algorithm for Detecting Known and Unknown Web Attacks, IEEE Access, 5, 26190, 10.1109/ACCESS.2017.2766844 Kanjo, 2018, Towards unravelling the relationship between on-body, environmental and emotion data using sensor information fusion approach, Inf. Fusion, 40, 18, 10.1016/j.inffus.2017.05.005 Kumar, 2018, A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases, Comput. Electr. Eng, 65, 222, 10.1016/j.compeleceng.2017.09.001 Kumar, 2018, Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier, Futur. Gener. Comput. Syst, 86, 527, 10.1016/j.future.2018.04.036 Kumar, 2017, Rough Set Theory and Fuzzy Logic Based Warehousing of Heterogeneous Clinical Databases, Int. J. Uncertainty, Fuzziness Knowlege-Based Syst, 25, 385, 10.1142/S0218488517500167 myoung Kwon, 2019, Deep learning for predicting in-hospital mortality among heart disease patients based on echocardiography, Echocardiography, 36, 213, 10.1111/echo.14220 Latha, 2019, Improving the accuracy of prediction of heart disease risk based on ensemble classification techniques, Informatics Med. Unlocked, 16, 10.1016/j.imu.2019.100203 Long, 2015, A highly accurate firefly based algorithm for heart disease prediction, Expert Syst. Appl, 42, 8221, 10.1016/j.eswa.2015.06.024 Manogaran, 2018, A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system, Futur. Gener. Comput. Syst, 82, 375, 10.1016/j.future.2017.10.045 Manogaran, 2018, Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System, Multimed. Tools Appl, 77, 4379, 10.1007/s11042-017-5515-y Melin, 2018, A hybrid model based on modular neural networks and fuzzy systems for classification of blood pressure and hypertension risk diagnosis, Expert Syst. Appl, 107, 146, 10.1016/j.eswa.2018.04.023 Mohan, 2019, Effective heart disease prediction using hybrid machine learning techniques, IEEE Access, 7, 81542, 10.1109/ACCESS.2019.2923707 Moon, 2019, Interpolation of greenhouse environment data using multilayer perceptron, Comput. Electron. Agric, 166, 10.1016/j.compag.2019.105023 Muzammal, 2020, A multi-sensor data fusion enabled ensemble approach for medical data from body sensor networks, Inf. Fusion, 53, 155, 10.1016/j.inffus.2019.06.021 Nandhu Kishore, 2018, Neuro-fuzzy based medical decision support system for coronary artery disease diagnosis and risk level prediction, J. Comput. Theor. Nanosci., 15, 1027, 10.1166/jctn.2018.7198 Narayan, 2019, A novel recommender system based on FFT with machine learning for predicting and identifying heart diseases, Neural Comput. Appl, 31, 93, 10.1007/s00521-018-3662-3 Nazari, 2018, A fuzzy inference- fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases, Expert Syst. Appl, 95, 261, 10.1016/j.eswa.2017.11.001 Nguyen, 2015, Classification of healthcare data using genetic fuzzy logic system and wavelets, Expert Syst. Appl, 42, 2184, 10.1016/j.eswa.2014.10.027 H.F. Nweke, Y.W. Teh, U.R. Alo, G. Mujtaba, Analysis of Multi-Sensor Fusion for Mobile and Wearable Sensor Based Human Activity Recognition, (2018) 22–26. Paul, 2018, Adaptive weighted fuzzy rule-based system for the risk level assessment of heart disease, Appl. Intell, 48, 1739, 10.1007/s10489-017-1037-6 Reddy, 2017, An efficient system for heart disease prediction using hybrid OFBAT with rule-based fuzzy logic model, J. Circuits, Syst. Comput., 26, 1, 10.1142/S021812661750061X Rehman, 2018, Intelligent hepatitis diagnosis using adaptive neuro-fuzzy inference system and information gain method, Soft Comput Samuel, 2017, An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction, Expert Syst. Appl, 68, 163, 10.1016/j.eswa.2016.10.020 Song, 2017, Development of a medical big-data mining process using topic modeling, Cluster Comput, 1 Stewart, 2019, Predicting mental health help seeking orientations among diverse Undergraduates: an ordinal logistic regression analysis✰, J. Affect. Disord., 257, 271, 10.1016/j.jad.2019.07.058 Terrada, 2019, A fuzzy medical diagnostic support system for cardiovascular diseases diagnosis using risk factors, 1 Tsinganos, 2018, On the comparison of wearable sensor data fusion to a single sensor machine learning technique in fall detection, Sensors (Switzerland), 18 Tuli, 2019, HealthFog: an Ensemble Deep Learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing Environments, Futur. Gerenation Comput. Syst Vijayakumar, 2019, Random forest for big data classification in the internet of things using optimal features, Int. J. Mach. Learn. Cybern, 0, 0 Xi, 2018, Feature-level fusion of surface electromyography for activity monitoring, Sensors (Switzerland), 18 Xu, 2019, An attribute value frequency-based instance weighting filter for naive Bayes, J. Exp. Theor. Artif. Intell., 31, 225, 10.1080/0952813X.2018.1544284 Yin, 2017, A Health Decision Support System for Disease Diagnosis Based on Wearable Medical Sensors and Machine Learning Ensembles, IEEE Trans. Multi-Scale Comput. Syst, 3, 228, 10.1109/TMSCS.2017.2710194 Zhang, 2017, Coupling a Fast Fourier Transformation with a Machine Learning Ensemble Model to Support Recommendations for Heart Disease Patients in a Telehealth Environment, IEEE Access, 5, 10674, 10.1109/ACCESS.2017.2706318