Intelligent Healthcare Systems

The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers' issues, software design, and biometrics, among other areas. Hence, solving 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. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare 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.

Vania V. Estrela has a B.S. degree from Federal University of Rio de Janeiro (UFRJ) in Electrical and Computer Engineering (ECE); M.Sc. from the Technological Institute of Aeronautics (ITA), Brazil; M.Sc. degree in ECE at Northwestern University, USA; and Ph.D. in ECE from the Illinois Institute of Technology (IIT), Chicago, IL, USA. Taught at DePaul University, USA, and Universidade Estadual do Norte Fluminense (UENF), Brazil. She was visiting professor at the Polytechnic Institute of Rio de Janeiro (IPRJ)/State University of Rio de Janeiro (UERJ) in Brazil and currently working at UFF's Department of Telecommunications. Research interests include signal/image/video processing, inverse problems, computational & mathematical modeling, stochastic models, multimedia, communications, motion estimation, machine learning, and geoprocessing. She reviews several journal/magazine articles, and she is deputy editor of the Neuroscience Informatics journal (Elsevier). She is engaged in technology transfer, STEAM education, environmental issues, and digital inclusion. She is editor of several books and special issues and a member of IEEE and ACM.

PART 1: INTELLIGENCE MEANINGS AND ROLES IN HEALTHCARE: INTRODUCTORY ASPECTS. Introduction to Intelligent Healthcare in a Post-Pandemic World. The Building Blocks of Health 4.0 - Internet of Things, Big Data with Cloud and Fog Computing. Internet of Medical Things (IoMT) Layers for Medical Cyber-Physical Systems. Ad Hoc Networks in Healthcare Intelligent Transportation Systems - MANETs, VANETs, and FANETs. Scale and Resolution Issues regarding Medical Images: Challenges Ahead. Some Issues regarding Content-Based Image Retrieval (CBIR) for Remote Healthcare Theradiagnosis. Blockchain Technology Enabling Better Services in the Healthcare Domain. 6G in Healthcare - Anticipating Needs and Requirements. PART 2: INFRASTRUCTURAL MEDICAL APPLICATIONS. Remote Sensing Applications in Disease Mapping and Public Health Analysis. On DICOM, HEVC and 3D Medical Image Compression for Volumetric Theragnostics. Deep Learning as a Drive Force for Better Drug Development. In-Body Devices and Sensors Communication - How Implantables, Ingestibles, and Injectables Interact with the Internet. Nanotechnology, Internet of Nano-things and Nanorobotics in Healthcare - Nano for All. Digital Twin Framework for Intelligent Healthcare Facilities through ISO/IEEE 11073. PART 3: ADVANCED APPLICATIONS USING AI. Medical Visual Theragnostic Systems Using Artificial Intelligence (AI) - Principles and Perspectives. Metaheuristics Applied to Pathology Image Analysis. Mobile Agents and Blockchain for Robust and Secure Authentication and Access Control in Healthcare Systems. Super-resolution Image Processing for Hemoglobin Quantification: A Case Study. BrATCat: Data Augmentation of MRI Scans via Image-to-Image Translation using CycleGAN Followed by Pre-Trained Model Categorization.