Proceedings of the Fourth International Conference on Health GIS, held at New Delhi during 5-6 August 2011.

Although many books have been published on the application of GIS in emergency management and disaster response, this is the first one to bring together a comprehensive discussion of the critical role GIS plays in hospital and healthcare emergency management and disaster response. Illustrating a wide range of practical applications, GIS in Hospital

The book introduces a variety of latest techniques designed to represent, enhance, and empower multi-disciplinary approaches of geographic information system (GIS), artificial intelligence (AI), deep learning (DL), machine learning, and cloud computing research in healthcare. It provides a unique compendium of the current and emerging use of geospatial data for healthcare and reflects the diversity, complexity, and depth and breadth of this multi-disciplinary area. This book addresses various aspects of how smart healthcare devices can be used to detect and analyze diseases. Further, it describes various tools and techniques to evaluate the efficacy, suitability, and efficiency of geospatial data for health-related applications. It features illustrative case studies, including future applications and healthcare challenges. This book is beneficial for computer science and engineering students and researchers, medical professionals, and anyone interested in using geospatial data in healthcare. It is also intended for experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious to learn about this important subject. The book presents an effort to draw how we can build health-related applications using geospatial big data and their subsequent analysis.

This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes. Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamics Offers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many more Includes the latest technological advances in the IoT and deep learning with their implementations in healthcare Combines deep learning and analysis in the unified framework to understand both IoT and deep learning applications Covers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challenges Postgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful.

Turbulent changes in worldwide economies and decreases in overall quality of life have led to a re-evaluation of the current state of health services. Improvements in this sector will allow for more efficient healthcare delivery to the public, as well as increased patient satisfaction. Effective Methods for Modern Healthcare Service Quality and Evaluation is an authoritative reference source for the latest research on emerging tools and methodologies for the design of healthcare models, providing expert analyses on trouble-shooting specific problems in the industry and creating optimal hospital environments. Highlighting various perspectives across a range of relevant health services, this book is ideally designed for policy makers, researchers, upper-level students, and practitioners.

User-Driven Healthcare: Concepts, Methodologies, Tools, and Applications provides a global discussion on the practice of user-driven learning in healthcare and connected disciplines and its influence on learning through clinical problem solving. This book brings together different perspectives for researchers and practitioners to develop a comprehensive framework of user-driven healthcare.

The use of mobile devices in medical care settings and by wellness professionals has influenced and changed many aspects of clinical practice. Mobile devices have become ubiquitous in these settings, leading to rapid growth in the development of medical apps. Contemporary Applications of Mobile Computing in Healthcare Settings is a critical scholarly resource that explores the benefits of using mobile devices and apps in the medical field and examines the shortcomings in the validation practices regarding these technologies. Featuring coverage on a wide range of topics such as smart healthcare, patient surveillance, and body fitness monitoring, this book is geared toward academicians, nurses, medical professionals, practitioners, and students seeking current research on the quality and safety of the apps currently available for use by medical care professionals.