Optimizing Healthcare through Computational Intelligence and Deep Learning

Author Vania V. Estrela’s groundbreaking book delves into the intricate world of medical cyber-physical systems, shedding light on the myriad of challenges and opportunities presented by image processing, microscopy, security, biomedical imaging, automation, robotics, network layers issues, software design, and biometrics.

The book addresses the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. It presents lighter computational implementations as a potential solution to circumvent the heavy computational burden of healthcare processing applications.

Soft computing, metaheuristic, and deep learning emerge as potential solutions to efficient super-resolution deployment. The increasing amount of multi-resolution and multi-modal images necessitates more efficient and intelligent analyses, such as computer-aided diagnosis via computational intelligence techniques.

This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare, aiming to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems design practices and computational intelligence tactics for medical usage.

The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.

With a focus on the latest research and technologies, this book is an essential read for anyone interested in the intersection of healthcare and technology. It offers insights into the future of healthcare and the role of computational intelligence and deep learning in shaping it.