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Sharif, M. M., Alaa Tharwat, A. E. Hassanien, and H. A. Hefny, "Enzyme Function Classification: Reviews, Approaches, and Trends", Handbook of Research on Machine Learning Innovations and Trends: IGI Global, pp. 161–186, 2017. Abstract
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Sharif, M. M., Alaa Tharwat, A. E. Hassanien, and H. A. Hefny, "Enzyme Function Classification: Reviews, Approaches, and Trends: ", Handbook of Research on Machine Learning Innovations and Trends , USA, IGI, USA pp. 26 , 2017. Abstract

Enzymes are important in our life and it plays a vital role in the most biological processes in the living organisms and such as metabolic pathways. The classification of enzyme functionality from a sequence, structure data or the extracted features remains a challenging task. Traditional experiments consume more time, efforts, and cost. On the other hand, an automated classification of the enzymes saves efforts, money and time. The aim of this chapter is to cover and reviews the different approaches, which developed and conducted to classify and predict the functions of the enzyme proteins in addition to the new trends and challenges that could be considered now and in the future. The chapter addresses the main three approaches which are used in the classification the function of enzymatic proteins and illustrated the mechanism, pros, cons, and examples for each one.

Sharif, M. M., Alaa Tharwat, A. E. Hassanien, and H. A. Hefny, "Enzyme vs. non-enzyme classification based on principal component analysis and AdaBoost classifier", Computing, Communication and Automation (ICCCA), 2016 International Conference on: IEEE, pp. 288–293, 2016. Abstract
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Awad, A. I., and A. E. Hassanien, "Erratum: Impact of Some Biometric Modalities on Forensic Science", Computational Intelligence in Digital Forensics: Forensic Investigation and Applications: Springer International Publishing, pp. E1–E1, 2014. Abstract
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Hussein, H. K., A. - E. Hassanien, and M. Nakajima, "Escape-Time Modified Algorithm for Generating Fractal Images Based on Petri Net Reachability", IEICE TRANSACTIONS on Information and Systems, vol. 82, no. 7: The Institute of Electronics, Information and Communication Engineers, pp. 1101–1108, 1999. Abstract
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Abder-Rahman Ali, Micael Couceiro, A. M. Anter, and A. E. Hassanien, "Evaluating an Evolutionary Particle Swarm Optimization for Fast Fuzzy C-Means Clustering on Liver CT Images", Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies, USA, IGI, 2014. Abstract

An Evolutionary Particle Swarm Optimization based on the Fractional Order Darwinian method for
optimizing a Fast Fuzzy C-Means algorithm is proposed. This chapter aims at enhancing the performance
of Fast Fuzzy C-Means, both in terms of the overall solution and speed. To that end, the concept
of fractional calculus is used to control the convergence rate of particles, wherein each one of them
represents a set of cluster centers. The proposed solution, denoted as FODPSO-FFCM, is applied on
liver CT images, and compared with Fast Fuzzy C-Means and PSOFFCM, using Jaccard Index and
Dice Coefficient. The computational efficiency is achieved by using the histogram of the image intensities
during the clustering process instead of the raw image data. The experimental results based on the
Analysis of Variance (ANOVA) technique and multiple pair-wise comparison show that the proposed
algorithm is fast, accurate, and less time consuming.

Sarkar, M., S. Banerjee, and A. E. Hassanien, "Evaluating the Degree of Trust Under Context Sensitive Relational Database Hierarchy Using Hybrid Intelligent Approach", International Journal of Rough Sets and Data Analysis (IJRSDA), vol. 2, no. 1: IGI Global, pp. 1–21, 2015. Abstract
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Mostafa, A., H. Hefny, N. I. Ghali, A. E. Hassanien, and G. Schaefer, "Evaluating the effects of image filters in CT liver CAD system", Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on: IEEE, pp. 448–451, 2012. Abstract
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Mostafa, A., H. Hefny, N. I. Ghali, A. E. Hassanien, and G. Schaefer, "Evaluating the effects of image filters in CT liver CAD system", Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on: IEEE, pp. 448–451, 2012. Abstract
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Mostafa, A., H. Hefny, N. I. Ghali, A. E. Hassanien, and G. Schaefer, "Evaluating the effects of image filters in CT liver CAD system", Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on: IEEE, pp. 448–451, 2012. Abstract
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Moftah, H. M., W. H. Elmasry, N. El-Bendary, A. E. Hassanien, and K. Nakamatsu, "Evaluating the effects of k-means clustering approach on medical images", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 455–459, 2012. Abstract
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Moftah, H. M., W. H. Elmasry, N. El-Bendary, A. E. Hassanien, and K. Nakamatsu, "Evaluating the effects of k-means clustering approach on medical images", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 455–459, 2012. Abstract
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Sarkar, M., S. Banerjee, and A. E. Hassanien, "Evaluating the Propagation Strength of Malicious Metaphor in Social Network: Flow Through Inspiring Influence of Members", Social Networking, London, Intelligent Systems Reference Library Springer, 2014.
Sarkar, M., S. Banerjee, and A. E. Hassanien, "Evaluating the Propagation Strength of Malicious Metaphor in Social Network: Flow Through Inspiring Influence of Members", Social Networking: Springer International Publishing, pp. 201–213, 2014. Abstract
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Mohamed Tahoun, Abd El Rahman Shabayek, A. E. Hassanien, and R. Reulke, "An Evaluation of Local Features on Satellite Images ", The 37th International Conference on Telecommunications and Signal Processing (TSP), which will be held during 2014, ., Berlin, Germany, July 1-3,, 2014. tahoun_shabayek_abo_reulke_tsp2014_berlin.pdf
Mohamed Tahoun, Abd El Rahman Shabayek, A. E. Hassanien, and R. Reulke, "An evaluation of local features on satellite images", Telecommunications and Signal Processing (TSP), 2015 38th International Conference on: IEEE, pp. 1–6, 2015. Abstract
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Ayeldeen, H., A. E. Hassanien, and A. Fahmy, "Evaluation of Semantic Similarity across MeSH Ontology: A Cairo University Thesis Mining Case Study", 12th Mexican International Conference on Artificial Intelligence, , Mexico City, Mexico, pp. 139-144, 2013.
Ayeldeen, H., A. E. Hassanien, and A. A. Fahmy, "Evaluation of semantic similarity across MeSH ontology: a Cairo University thesis mining case study", Artificial Intelligence (MICAI), 2013 12th Mexican International Conference on: IEEE, pp. 139–144, 2013. Abstract
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Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and T. - H. Kim, "Event detection based approach for soccer video summarization using machine learning", Int J Multimed Ubiquitous Eng, vol. 7, no. 2, pp. 63–80, 2012. Abstract
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Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and T. - H. Kim, "Event detection based approach for soccer video summarization using machine learning", Int J Multimed Ubiquitous Eng, vol. 7, no. 2, pp. 63–80, 2012. Abstract
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Abdo, W., Evolutionary Computation in Cryptanalysis, , Cairo Egypt, Al Azhar University and Scientific Research Group in Egypt (SRGE), 2013. ppt_phd_thesis_on_EC_CA.pdfphd_thesis_EC_CA_2013.pdf
Azar, A. T., A. E. Hassanien, T. - H. Kim, and others, "Expert system based on neural-fuzzy rules for thyroid diseases diagnosis", Computer Applications for Bio-Technology, Multimedia, and Ubiquitous City: Springer Berlin Heidelberg, pp. 94–105, 2012. Abstract
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Azar, A. T., A. E. Hassanien, T. - H. Kim, and others, "Expert system based on neural-fuzzy rules for thyroid diseases diagnosis", Computer Applications for Bio-Technology, Multimedia, and Ubiquitous City: Springer Berlin Heidelberg, pp. 94–105, 2012. Abstract
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Azar, A. T., A. E. Hassanien, T. - H. Kim, and others, "Expert system based on neural-fuzzy rules for thyroid diseases diagnosis", Computer Applications for Bio-Technology, Multimedia, and Ubiquitous City: Springer Berlin Heidelberg, pp. 94–105, 2012. Abstract
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Ahmad. Taher Azar, A. E. Hassanien, and T. - H. Kim, "Expert System Based On Neural-Fuzzy Rules for Thyroid Diseases Diagnosis.", International Conference on Bio-Science and Bio-Technology (BSBT2012), , Kangwondo, Korea. pp. 94--105, December 16-19, 2012. Abstract3530094.pdf

The thyroid, an endocrine gland that secretes hormones in the blood, circulates its products to all tissues of the body, where they control vital functions in every cell. Normal levels of thyroid hormone help the brain, heart, intestines, muscles and reproductive system function normally. Thyroid hormones control the metabolism of the body. Abnormalities of thyroid function are usually related to production of too little thyroid hormone (hypothyroidism) or production of too much thyroid hormone (hyperthyroidism). Therefore, the correct diagnosis of these diseases is very important topic. In this study, Linguistic Hedges Neural-Fuzzy Classifier with Selected Features (LHNFCSF) is presented for diagnosis of thyroid diseases. The performance evaluation of this system is estimated by using classification accuracy and k-fold cross-validation. The results indicated that the classification accuracy without feature selection was 98.6047% and 97.6744% during training and testing phases, respectively with RMSE of 0.02335. After applying feature selection algorithm, LHNFCSF achieved 100% for all cluster sizes during training phase. However, in the testing phase LHNFCSF achieved 88.3721% using one cluster for each class, 90.6977% using two clusters, 91.8605% using three clusters and 97.6744% using four clusters for each class and 12 fuzzy rules. The obtained classification accuracy was very promising with regard to the other classification applications in literature for this problem.