Artificial Intelligence Theory, Models, and Applications

This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: - Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world - A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization - The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine - AI's role in the diagnosis of various diseases, such as cancer and diabetes - The role of machine learning models in product development and statistically monitoring product quality - Machine learning to make robust and effective economic policy decisions - Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.

Prof. P. Kaliraj is the Vice-Chancellor of Bharathiar University, Coimbatore, India. Prof. T. Devi is the dean of faculty of research at the Department of Computer Applications, Bharathiar University, Coimbatore, India.

Preface. Acknowledgments. Editors. Contributors. Chapter 1 Artificial Intelligence: A Complete Insight. Chapter 2 Artificial Intelligence and Gender. Chapter 3 Artificial Intelligence in Environmental Management. Chapter 4 Artificial Intelligence in Medical Imaging. Chapter 5 Artificial Intelligence (AI) - Improving Customer Experience (CX). Chapter 6 Artificial Intelligence in Radiotherapy. Chapter 7 Artificial Intelligence in Systems Biology: Opportunities in Agriculture, Biomedicine, and Healthcare. Chapter 8 Artificial Intelligence Applications in Genetic Disease/Syndrome Diagnosis. Chapter 9 Artificial Intelligence in Disease Diagnosis via Smartphone Applications. Chapter 10 Artificial Intelligence in Agriculture. Chapter 11 Artificial Intelligence-Based Ubiquitous Smart Learning Educational Environments. Chapter 12 Artificial Intelligence in Assessment and Evaluation of Programme Outcomes/Programme Specific Outcomes. Chapter 13 Artificial Intelligence-Based Assistive Technology. Chapter 14 Machine Learning. Chapter 15 Machine Learning in Human Resource Management. Chapter 16 Machine Learning Models in Product Development and its Statistical Evaluation. Chapter 17 Influence of Artificial Intelligence in Clinical and Genomic Diagnostics. Chapter 18 Applications of Machine Learning in Economic Data Analysis and Policy Management. Chapter 19 Industry 4.0: Machine Learning in Video Indexing. Chapter 20 A Risk-Based Ensemble Classifier for Breast Cancer Diagnosis. Chapter 21 Linear Algebra for Machine Learning. Chapter 22 Identification of Lichen Plants and Butterflies Using Image Processing and Neural Networks in Cloud Computing. Chapter 23 Artificial Neural Network for Decision Making. Index.

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