Titlebook: Enabling AI Applications in Data Science; Aboul-Ella Hassanien,Mohamed Hamed N. Taha,Nour El Book 2021 The Editor(s) (if applicable) and T

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Boosting Traditional Healthcare-Analytics with Deep Learning AI: Techniques, Frameworks and Challengal data, patient behavior data etc. to leverage insights for making more informed decisions, improve patient care and services at various levels of the organization. Traditional Machine Learning techniques are limited in their ability to process and extract feature from raw data. Over the last coupl

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Factors Influencing Electronic Service Quality on Electronic Loyalty in Online Shopping Context: Dat quality, decision-makers of organizations with Web presences must first realize how customers develop online customer loyalty. In-formation about this topic limited from both academic and practitioner sources; however, this information should be examined in multi-context by using multiple e-SQ dime

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Stochastic SPG with Minibatchesc distance to optimal solution, after . iterations, for a constant minibatch size .. The numerical tests on .–regularized SVMs and parametric sparse representation problems confirm the theoretical behaviour and surpasses minibatch SGD performance.

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The Human Mental Search Algorithm for Solving Optimisation Problemsof a candidate solution, the grouping operator employs an unsupervised clustering technique, .-means, to partition candidate solutions, while the movement operator moves candidate solutions towards a promising area identified by the grouping operator. To evaluate the efficacy of the HMS algorithm, a

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An Automatic Classification of Genetic Mutations by Exploring Different Classifierstechniques to convert text entry to numerical form, after which they are fed as input to different classifiers. Logistic Regression classifier with Term Frequency—Inverse Document Frequency encoding technique fetched the maximum accuracy, i.e. 67.27%. Attention had been given to enhance this accurac

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In Depth Analysis, Applications and Future Issues of Artificial Neural Networkd storage, robustness, non linear nature, tolerance to failure, handling of fuzzy information and their in and the generalization ability. Thus, ANN being of prime importance in the era of technological advancements, this paper aims at providing an in-depth understanding of the neural network, its m

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