Mathematical Modeling in Computational Intelligence and Generative AI: CIGAI-2025, Hyderabad, India, June 19-20

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Bol 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. 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.

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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. 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.


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