Cutting Edge Artificial Intelligence Advances And Implications In Real World Applications
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Cutting-Edge Artificial Intelligence Advances and Implications in Real-World Applications
Artificial intelligence (AI) is impacting industries worldwide by introducing new methods and altering traditional practices. This book examines AI’s diverse effects, providing insights into its applications, challenges, and future prospects across education, healthcare, finance, and more. The chapters explore how AI technologies, such as large language models, enhance feedback in higher education and influence legal studies while upholding academic integrity. A review of key technical approaches—knowledge-based systems, machine learning, and intelligent optimization—lays the groundwork for understanding AI’s potential. Real-world examples illustrate AI’s role in medical imaging, presenting new diagnostic methods and the use of language models for image interpretation. The book also discusses financial applications, including techniques for credit card fraud detection and forecasting natural gas prices using innovative models. Additionally, it covers personalized federated learning models, highlighting the importance of data privacy and security in AI’s evolution. This comprehensive guide is valuable for educators, researchers, practitioners, and students interested in AI’s current and future developments. By combining theory with practical examples, the book offers readers a clear understanding of how AI affects various sectors, enabling them to engage effectively with this rapidly evolving field.
Proceedings of World Conference on Artificial Intelligence: Advances and Applications
Author: Ashish Kumar Tripathi
language: en
Publisher: Springer Nature
Release Date: 2024-09-30
This book is a collection of outstanding research papers presented at the World Conference on Artificial Intelligence: Advances and Applications (WCAIAA 2024), organized by Sir Padampat Singhania University, India, and is technically sponsored by Soft Computing Research Society during February 22–23, 2024. The topics covered are agent-based systems, evolutionary algorithms, approximate reasoning, bioinformatics and computational biology, artificial intelligence in modeling and simulation, natural language processing, brain–machine interfaces, collective intelligence, computer vision and speech understanding, data mining, swarm intelligence, machine learning, human–computer interaction, intelligent sensor, devices and applications, and intelligent database systems.
Artificial Intelligence in Healthcare
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data