Efren Mezura-Montes – författare

AI-Powered Insurance is a comprehensive exploration of how Artificial Intelligence is revolutionizing the global insurance industry. This book brings together cutting-edge research and real-world case studies, covering AI''s transformative impact across underwriting, risk management, customer experience, and policy personalization. It examines emerging technologies, ethical challenges, and security concerns while analyzing machine learning applications in insurance policy evaluation. From automation versus human expertise to bibliometric research trends, the book offers diverse perspectives from leading experts. An essential resource for researchers, practitioners, and policymakers, it charts the future of intelligent, data-driven insurance in an increasingly digital world.

AI-Powered Insurance is a comprehensive exploration of how Artificial Intelligence is revolutionizing the global insurance industry. This book brings together cutting-edge research and real-world case studies, covering AI''s transformative impact across underwriting, risk management, customer experience, and policy personalization. It examines emerging technologies, ethical challenges, and security concerns while analyzing machine learning applications in insurance policy evaluation. From automation versus human expertise to bibliometric research trends, the book offers diverse perspectives from leading experts. An essential resource for researchers, practitioners, and policymakers, it charts the future of intelligent, data-driven insurance in an increasingly digital world.

The proceedings of MICAI 2023 workshops are structured into three sections:

– HIS 2023: 16th Workshop of Hybrid Intelligent Systems

– CIAPP 2023: 5th Workshop on New Trends in Computational Intelligence and Applications

This book constitutes the proceedings of the 16th Mexican Conference on Pattern Recognition, MCPR 2024, held in Xalapa, Mexico, during June 19–22, 2024, Proceedings.

The 36 full papers were carefully reviewed and selected from 68 submissions. The papers are organized in subject areas as follows: Pattern Recognition and Machine Learning Techniques; Computer Vision; Medical Applications of Pattern Recognition; Language Processing and Recognition; Deep Learning and Neural Networks.

The book also provides critical review of the contemporary constraint handling approaches. The contributions of the book may further help to explore new avenues leading towards multidisciplinary research discussions. This book is a complete reference for engineers, scientists, and students studying/working in the optimization, artificial intelligence (AI), or computational intelligence arena.