RETRACTED ARTICLE: Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System

Agboizebeta IA, Chukwuyeni OJ (2012a) Application of neuro-fuzzy expert systemfor the probe and prognosis of thyroid disorder. Int J Fuzzy Logic Syst 2(2)

Agboizebeta IA, Chukwuyeni OJ (2012b) Cognitive neuro-fuzzy expert system forhypotension control. Comput Eng Intell Syst 3(6):21–32

Alamelumangai N, DeviShree J (2010) PSO aided neuro fuzzy inference system forultrasound image segmentation. Int J Comput Appl 7(14)

Alfarhan KA, Mashor MY, Saad M, Rahman A, Azeez HA, Sabry MM (2017) Effects of the Window Size and Feature Extraction Approach for Arrhythmia Classification. In: Journal of Biomimetics, Biomaterials and Biomedical Engineering, vol 30. Trans Tech Publications, pp 1–11

Austin PC, Tu JV, Ho JE, Levy D, Lee DS (2013) Using methods from the data-mining and machine-learning literature for disease classification and prediction: a case study examining classification of heart failure subtypes. J Clin Epidemiol 66(4):398–407

Cao J, Yu S, Liu H, Li P (2016) Hand posture recognition based on heterogeneous features fusion of multiple kernels learning. Multimed Tools Appl 75(19):11909–11928

Comak E, Arslan A, Türkoğlu I (2007) A decision support system based on support vector machines for diagnosis of the heart valve diseases. Comput Biol Med 37:21–27

Dou W, Ruan S, Chen Y, Bloyet D, Constans JM (2007) A framework of fuzzy information fusion for the segmentation of brain tumor tissues on MR images. Image Vis Comput 25(2):164–171

Ephzibah EP, Sundarapandian V (2012) An expert system for heart disease diag-nosis using neuro-fuzzy technique. Int J Soft Comput Artif Intell Appl 1(1)

Gijzen H (2013) Development: big data for a sustainable future. Nature 502(7469):38–38

Guler I, Ubeyli ED (2005) Adaptive neuro-fuzzy inference system for classificationof EEG signals using wavelet coefficients. J Neurosci Methods 148(2):113–121

Hampton SE, Strasser CA, Tewksbury JJ, Gram WK, Budden AE, Batcheller AL et al (2013) Big data and the future of ecology. Front Ecol Environ 11(3):156–162

Jang SM, Hart PS (2015) Polarized frames on ―climate change‖ and ―global warming‖ across countries and states: evidence from twitter big data. Glob Environ Chang 32:11–17

Jiang H, Tian Y (2011) Fuzzy image fusion based on modified Self-Generating Neural Network. Expert Syst Appl 38(7):8515–8523

Khameneh NB, Arabalibeik H, Salehian P, Setayeshi S (2012) Abnormal red bloodcells detection using adaptive neuro-fuzzy system. Stud Health Technol Inform 173:30–34

Kumar PM, Gandhi UD (2017) A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases. Comput Electr Eng

Kumar KA, Punithavalli M (2011) Efficient cancer classification using fast adap-tive neuro-fuzzy inference system (FANFIS) based on statistical techniques. Int J Adv Comput Sci Appl Spec Issue Artif Intell 132–137

Kumar PM, Gandhi U, Varatharajan R, Manogaran G, Jidhesh R, Vadivel T (2017) Intelligent face recognition and navigation system using neural learning for smart security in Internet of Things. Cluster Computing 1–12. https://doi.org/10.1007/s10586-017-1323-4

Lopez D, Gunasekaran M (2015) Assessment of Vaccination Strategies Using Fuzzy Multi-criteria Decision Making. In: Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO-2015). Springer, pp 195–208

Lopez D, Gunasekaran M, Murugan BS, Kaur H, Abbas KM (2014) Spatial Big Data analytics of influenza epidemic in Vellore, India. In: Big Data (Big Data), 2014 I.E. International Conference on. IEEE, pp 19–24

Lopez D, Manogaran G (2016) Big Data Architecture for Climate Change and Disease Dynamics. In: Geetam S. Tomar et al (eds) The Human Element of Big Data: Issues, Analytics, and Performance. CRC Press

Lopez D, Manogaran G (2017) Parametric model to predict H1N1 influenza in vellore district. In: Handbook of Statistics, vol 37. Elsevier, Tamil Nadu, India, pp 301–316

Lopez D, Manogaran G, Jagan J (2017) Modelling the H1N1 influenza using mathematical and neural network approaches. Biomed Res 28(8):1–5

Lopez D, Sekaran G (2016) Climate change and disease dynamics-A Big Data perspective. Int J Infect Dis 45:23–24

Luo Z, Wu M, Zhao Y (2015) Big Data Applications in Biomedical Informatics, (In Chinese). J Med Inform 36(5):2–9

Luo J, Wu M, Zhao Y (2016) Big Data Application in Biomedical Research and Health Care: A Literature Review. Biomed Inf Insights 8:1

Manogaran G, Lopez D (2017a) Disease surveillance system for big climate data processing and dengue transmission. Int J Ambient Comput Intell (IJACI) 8(2):88–105

Manogaran G, Lopez D (2017b) Spatial cumulative sum algorithm with big data analytics for climate change detection. Comput Electr Eng. doi:https://doi.org/10.1016/j.compeleceng.2017.04.006

Manogaran G, Lopez D (2017c). A Gaussian process based big data processing framework in cluster computing environment. Clust Comput :1–16

Manogaran G, Lopez D (2017d) A survey of big data architectures and machine learning algorithms in healthcare. Int J Biomed Eng Technol 25(3):182–211

Manogaran G, Lopez D, Thota C, Abbas KM, Pyne S, Sundarasekar R (2017) Big data analytics in healthcare Internet of Things. In: Innovative Healthcare Systems for the 21st Century. Springer International Publishing, pp. 263–284

Manogaran G, Thota C, Kumar MV (2016) MetaCloudDataStorage architecture for Big Data security in cloud computing. Procedia Comput Sci 87:128–133

Manogaran G, Thota C, Lopez D (2018) Human-Computer Interaction With Big Data Analytics. In: HCI Challenges and Privacy Preservation in Big Data Security. IGI Global, pp 1–22

Manogaran G, Thota C, Lopez D, Sundarasekar R (2017) Big Data Security Intelligence for Healthcare Industry 4.0. In: Cybersecurity for Industry 4.0. Springer International Publishing, pp 103–126

Manogaran G, Thota C, Lopez D, Vijayakumar V, Abbas KM, Sundarsekar R (2017a) Big Data Knowledge System in Healthcare. In: Internet of Things and Big Data Technologies for Next Generation Healthcare. Springer International Publishing, pp 133–157

Manogaran G, Varatharajan R, Lopez D, Kumar PM, Sundarasekar R, Thota C (2017b) A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting. Futur Gener Comput Syst 80(5):1–10

Manogaran G, Vijayakumar V, Varatharajan R, Kumar PM, Sundarasekar R, Hsu CH (2017c) Machine learning based big data processing framework for cancer diagnosis using hidden markov model and GM clustering. Wirel Pers Commun 1–18. https://doi.org/10.1007/s11277-017-5044-z

Mastorocostas PA, Hilas CS (2004) A dynamic fuzzy-neural filter for the analysis oflung sounds. IEEE Int Conf Syst Man Cybern 3:2231–2236

Mastorocostas PA, Theocharis JB (2005) A recurrent fuzzy-neural filter for real-time separation of lung sounds. Proc IEEE Int Joint Conf Neural Netw 5:3023–3028

Neagoe VE, Latin LF, Grunwald S (2003) A neuro-fuzzy approach to classification of ECG signals for ischemic heart disease diagnosis. In: AMIA Annual SymposiumProceedings, pp 494–498

Obi JC, Imainvan AA (2011a) Decision support system for the intelligient identi-fication of Alzheimer using neuro fuzzy logic. Int J Soft Comput 2(2):25–38

Obi JC, Imainvan AA (2011b) Interactive neuro-fuzzy expert system for diagnosis ofleukemia. Global J Comput Sci Technol 11(12)

Ovreiu M, Simon D (2010) Biogeography-Based Optimization of Neuro-FuzzySystem Parameters for Diagnosis of Cardiac Disease. In: Genetic and Evo-lutionary Computation Conference (GECCO)‘10. Portland, pp. 1235–1242

Oweis RJ, Sunna MJ (2005) A combined neuro–fuzzy approach for classifyingimage pixels in medical applications. J Electr Eng 56(5–6):146–150

Polat K, Gunes K (2007) An expert system approach based on principal componentanalysis and adaptive neuro-fuzzy inference system to diagnosis of diabetesdisease. Digit Signal Process 17(4):702–710

Priyan MK, Devi GU (2017) Energy efficient node selection algorithm based on node performance index and random waypoint mobility model in internet of vehicles. Clust Comput :1–15

Saeedi J, Faez K (2012) Infrared and visible image fusion using fuzzy logic and population-based optimization. Appl Soft Comput 12(3):1041–1054

Sengur A (2008) An expert system based on linear discriminant analysis and adap-tive neuro-fuzzy inference system to diagnosis heart valve diseases. Expert Syst Appl 35(1–2):214–222

Son SY, Lee SH, Chung K, Lim JS (2015) Feature selection for daily peak load forecasting using a neuro-fuzzy system. Multimed Tools Appl 74(7):2321–2336

Stavrakoudis D, Mastorocostas P, Theocharis J (2007) A pipelined recurrent fuzzy neural filter for the separation of lung sounds. Proc Fuzzy Syst Conf FUZZY-IEEE IEEE Int :1–6

Subasi A (2006) Automatic detection of epileptic seizure using dynamic fuzzy neuralnetworks. Expert Syst Appl 31(2):320–328

Thota C, Manogaran G, Lopez D, Vijayakumar V (2017) Big Data Security Framework for Distributed Cloud Data Centers. In: Cybersecurity Breaches and Issues Surrounding Online Threat Protection. IGI Global, pp 288–310

Thota C, Sundarasekar R, Manogaran G, Varatharajan R, Priyan MK (2018) Centralized Fog Computing Security Platform for IoT and Cloud in Healthcare System. In: Exploring the Convergence of Big Data and the Internet of Things. IGI Global, pp 141–154

Tripoliti EE, Papadopoulos TG, Karanasiou GS, Naka KK, Fotiadis DI (2017) Heart Failure: Diagnosis, Severity Estimation and Prediction of Adverse Events Through Machine Learning Techniques. Comput Struct Biotechnol J 15:26–47

Turkoglu I, Arslan A, Ilkay E (2002) An expert system for diagnosis of the heart valve diseases. Expert Syst Appl 23:229–236

Ubeyli ED (2009) Adaptive neuro-fuzzy inference system for classification of ECGsignals using Lyapunov exponents. Comput Methods Prog Biomed 93(3):313–321

Uguz H, Arslan A, Türkoğlu I (2007) A biomedical system based on hidden Markov model for diagnosis of the heart valve diseases. Pattern Recogn Lett. Available online 11 October, 2006

Varatharajan R, Manogaran G, Priyan MK (2017a) A big data classification approach using LDA with an enhanced SVM method for ECG signals in cloud computing. Multimedia Tools and Applications 1–21. https://doi.org/10.1007/s11042-017-5318-1

Varatharajan R, Manogaran G, Priyan MK, Balaş VE, Barna C (2017b) Visual analysis of geospatial habitat suitability model based on inverse distance weighting with paired comparison analysis. Multimed Tools Appl :1–21

Varatharajan R, Manogaran G, Priyan MK, Sundarasekar R (2017c) Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm. Clust Comput :1–10

Varatharajan R, Vasanth K, Gunasekaran M, Priyan M, Gao XZ (2017) An adaptive decision based kriging interpolation algorithm for the removal of high density salt and pepper noise in images. Comput Electr Eng

Vayena E, Salathé M, Madoff LC, Brownstein JS (2015) Ethical challenges of big data in public health. PLoS Comput Biol 11(2):e1003904

Wang R, Du H, Zhou F, Deng D, Liu Y (2014) An adaptive neural fuzzy network clothing comfort evaluation model and application in digital home. Multimed Tools Appl 71(2):395–410

Wen J, Chang XW (2017) Success probability of the Babai estimators for box-constrained integer linear models. IEEE Trans Inf Theory 63(1):631–648

Wen J, Zhou Z, Wang J, Tang X, Mo Q (2016) A sharp condition for exact support recovery of sparse signals with orthogonal matching pursuit. IEEE Trans Signal Process

Xiao Y, Xia L (2016) Human action recognition using modified slow feature analysis and multiple kernel learning. Multimed Tools Appl 75(21):13041–13056

Yu J, Duan H (2013) Artificial bee colony approach to information granulation-based fuzzy radial basis function neural networks for image fusion. Optik-Int J Light Electron Optics 124(17):3103–3111