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Enabling AI Applications in Data Science

  • Book
  • © 2021

Overview

Editors:
  1. Aboul-Ella Hassanien

    1. Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

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  2. Mohamed Hamed N. Taha

    1. Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

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    You can also search for this editor in PubMed   Google Scholar

  3. Nour Eldeen M. Khalifa

    1. Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

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    You can also search for this editor in PubMed   Google Scholar

  • Provides a detailed overview on latest advancements and applications in the field of Applied Artificial Intelligence and Data Science
  • Demonstrates how AI applications have achieved great accuracy and performance with the help of the advancements in data processing and storage
  • Written by experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 911)

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About this book

This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.

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Keywords

Table of contents (28 chapters)

  1. Front Matter

    Pages i-ix
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  2. Artificial Intelligence and Optimization

    1. Front Matter

      Pages 1-1
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    2. Stochastic SPG with Minibatches

      • Andrei Pătraşcu, Ciprian Păduraru, Paul Irofti
      Pages 3-25

    3. The Human Mental Search Algorithm for Solving Optimisation Problems

      • Seyed Jalaleddin Mousavirad, Gerald Schaefer, Hossein Ebrahimpour-Komleh
      Pages 27-47

    4. Reducing Redundant Association Rules Using Type-2 Fuzzy Logic

      • Eman Abd El Reheem, Magda M. Madbouly, Shawkat K. Guirguis
      Pages 49-62

    5. Identifiability of Discrete Concentration Graphical Models with a Latent Variable

      • Mohamed Sharaf
      Pages 63-76

    6. An Automatic Classification of Genetic Mutations by Exploring Different Classifiers

      • Badal Soni, K. Suganya Devi, Angshuman Bora
      Pages 77-102

    7. Towards Artificial Intelligence: Concepts, Applications, and Innovations

      • Djamel Saba, Youcef Sahli, Rachid Maouedj, Abdelkader Hadidi, Miloud Ben Medjahed
      Pages 103-146

  3. Big Data and Artificial Intelligence Applications

    1. Front Matter

      Pages 147-147
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    2. In Depth Analysis, Applications and Future Issues of Artificial Neural Network

      • Badal Soni, Prachi Mathur, Angshuman Bora
      Pages 149-183

    3. Big Data and Deep Learning in Plant Leaf Diseases Classification for Agriculture

      • Mohamed Loey
      Pages 185-200

    4. Machine Learning Cancer Diagnosis Based on Medical Image Size and Modalities

      • Walid Al-Dhabyani, Aly Fahmy
      Pages 201-223

    5. Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis

      • Ivan Lorencin, Nikola Anđelić, Sandi Baressi Šegota, Jelena Musulin, Daniel Štifanić, Vedran Mrzljak et al.
      Pages 225-245

    6. Predicting Building-Related Carbon Emissions: A Test of Machine Learning Models

      • Emmanuel B. Boateng, Emmanuella A. Twumasi, Amos Darko, Mershack O. Tetteh, Albert P. C. Chan
      Pages 247-266

    7. Artificial Intelligence System for Breast Cancer Screening Based on Malignancy-Associated Changes in Buccal Epithelium

      • A. V. Andreichuk, N. V. Boroday, K. M. Golubeva, D. A. Klyushin
      Pages 267-285

    8. The Role of Artificial Intelligence in Company’s Decision Making

      • Djamel Saba, Youcef Sahli, Abdelkader Hadidi
      Pages 287-314

    9. The Virtues and Challenges of Implementing Intelligent ‘Student-Success-Centered’ System

      • Fatema Abdulrasool
      Pages 315-334

    10. Boosting Traditional Healthcare-Analytics with Deep Learning AI: Techniques, Frameworks and Challenges

      • Prabha Susy Mathew, Anitha S. Pillai
      Pages 335-365

    11. Factors Influencing Electronic Service Quality on Electronic Loyalty in Online Shopping Context: Data Analysis Approach

      • Ahlam Al-Khayyal, Muhammad Alshurideh, Barween Al Kurdi, Said A. Salloum
      Pages 367-378

  4. IOT within Artificial Intelligence and Data Science

    1. Front Matter

      Pages 379-379
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Editors and Affiliations

  • Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa

Bibliographic Information

  • Book Title: Enabling AI Applications in Data Science

  • Editors: Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-52067-0

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-52066-3Published: 24 September 2020

  • Softcover ISBN: 978-3-030-52069-4Published: 25 September 2021

  • eBook ISBN: 978-3-030-52067-0Published: 23 September 2020

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: IX, 650

  • Number of Illustrations: 66 b/w illustrations, 154 illustrations in colour

  • Topics: Data Engineering, Computational Intelligence, Artificial Intelligence

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