Mathematical Modeling in Computational Intelligence and Generative AI
CIGAI-2025, Hyderabad, India, June 19-20
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Beschreibung
This proceedings volume discusses topics on generative AI—one of the most trending topics and application in every field of science and engineering—and machine intelligence. Chapters of this proceedings were presented at the International Conference on Mathematical Modeling in Computational Intelligence and Generative AI (Math-CIGAI), held at Koneru Lakshmaiah Education Foundation, Hyderabad, India, from 19–20 June 2025. The book also discusses how to develop new products and automate the system by generating the new and improved models and improve decision making systems. It also discusses the applications of machine intelligence and generative AI in healthcare decision making, drug discovery, personalized care, synthetic data generation, automations, and many more. Topics on mathematical models such as adversarial networks and variational autoencoders are also discusses which are deployed to produce images for data augmentation, improving disease diagnosis and advanced medical imaging research areas. This volume is intended for researchers, academicians, and professionals.
This proceedings volume discusses topics on generative AI—one of the most trending topics and application in every field of science and engineering—and machine intelligence. Chapters of this proceedings were presented at the International Conference on Mathematical Modeling in Computational Intelligence and Generative AI (Math-CIGAI), held at Koneru Lakshmaiah Education Foundation, Hyderabad, India, from 19–20 June 2025. The book also discusses how to develop new products and automate the system by generating the new and improved models and improve decision making systems. It also discusses the applications of machine intelligence and generative AI in healthcare decision making, drug discovery, personalized care, synthetic data generation, automations, and many more. Topics on mathematical models such as adversarial networks and variational autoencoders are also discusses which are deployed to produce images for data augmentation, improving disease diagnosis and advanced medical imaging research areas. This volume is intended for researchers, academicians, and professionals.
Addresses healthcare challenges, using AI-powered solutions, in cancer, cardiovascular, pediatric and infectious disease Highlights solving real-world challenges like cancer diagnosis, equipment failure detection, farming and cybersecurity Explores next-gen AI concepts like agentic intelligence, self-evolving systems and swarm-based decision-making
Autor*in
Yu-Chen Hu
Themen in »Mathematical Modeling in Computational Intelligence and Generative AI«
mathematical modeling computational intelligence artificial intelligence machine learning generative AI graphical neural network random decision forest HaMobNet smart surveillance autoencoders tamper detection breast cancer skin cancer leukemia sustainable agriculture