First published in 1963, Advances in Parasitology contains comprehensive and up-to-date reviews in all areas of interest in contemporary parasitology. Advances in Parasitology includes medical studies of parasites of major influence, such as Plasmodium falciparum and trypanosomes. The series also contains reviews of more traditional areas, such as zoology, taxonomy, and life history, which shape current thinking and applications. The 2013 impact factor is 4.36.

In recent years, there have been significant progress in computational intelligence and image processing with machine learning and deep learning as important components of modern artificial intelligence. All these progresses face challenges in dealing with Covid-19 pandemic for detection and treatment.This comprehensive compendium provides not only updated advances of computational intelligence and image processing in the detection and treatment of Covid-19, but also other medical applications such as in cancer detection and cardiovascular diseases, etc. More traditional approaches such as 2D segmentation and 3D reconstruction are included.The useful reference text is an updated version of the edited title, Computer Vision in Medical Imaging (World Scientific, 2014) and its companion volume, Frontiers of Medical Imaging (World Scientific, 2015). The book is written for engineers, scientists and the medical community to meet the increased challenges in medical applications.

Digital healthcare is heterogeneous along the entire treatment pathway, ranging from monitoring applications and artificial-intelligence-based diagnostics, to support for virtual reality surgery. Since the introduction of the Digital Health Act in Germany in early 2020, there has been a push toward digital innovative solutions, especially in the outpatient sector. This book analyzes current digital health law from an economic perspective, combining theory with real-world applications. It examines both the incentives and market access pathways for digital solutions and the price effects brought about by the new regulatory framework in Germany. Further, it discusses the difficulties in pricing due to the monopolistic BfArM register and negotiations with the association of all German health insurance companies. The book addresses a wide range of topics, including incentives for innovation, specifics of digital health applications, reimbursement and financing options for digital health solutions. Lastly, it presents an outlook for the future and a comparison between Germany and other countries, namely the USA and Japan. Given its scope, this book will appeal to scholars of health economics, healthcare management and public health, as well as practitioners and professionals in the public health sector.

This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help of computing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression.

This book examines the most novel and state-of-the-art applications of biomaterials, with chapters that exemplify approaches with targeted drug delivery, diabetes, neurodegenerative diseases and cranioplasty implants. Expert contributors analyze biomaterials such as calcium phosphate, sol-gel and quenched glasses, metallic and polymer implants, bioactive glass, and polymer composites while also covering important areas such as the soft tissue replacement, apatites, bone regeneration and cell encapsulation. This book is appropriate for biomedical engineers, materials scientists, and clinicians who are seeking to implement the most advanced approaches and technologies with their patients.

The book, Transformation in Healthcare with Emerging Technologies, presents healthcare industrial revolution based on service aggregation and virtualisation that can transform the healthcare sector with the aid of technologies such as Artificial Intelligence (AI), Internet of Things (IoT), Bigdata and Blockchain. These technologies offer fast communication between doctors and patients, protected transactions, safe data storage and analysis, immutable data records, transparent data flow service, transaction validation process, and secure data exchanges between organizations. Features: * Discusses the Integration of AI, IoT, big data and blockchain in healthcare industry * Highlights the security and privacy aspect of AI, IoT, big data and blockchain in healthcare industry * Talks about challenges and issues of AI, IoT, big data and blockchain in healthcare industry * Includes several case studies It is primarily aimed at graduates and researchers in computer science and IT who are doing collaborative research with the medical industry. Industry professionals will also find it useful.

Presents key aspects in the development and the implementation of machine learning and deep learning approaches towards developing prediction tools, models, and improving medical diagnosis Discusses recent trends innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines deep learning theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities

Provides a comprehensive overview on the recent developments on clinical decision support systems, precision health and data science in medicine Examines the advancements, challenges and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Reviews melanoma detection by deep learning techniques

Tremendous growth in healthcare treatment techniques and methods has led to the emergence of numerous storage and communication problems and need for security among vendors and patients. This book brings together latest applications and state-of-the-art developments in healthcare sector using Blockchain technology. It explains how blockchain can enhance security, privacy, interoperability, and data accessibility including AI with blockchains, blockchains for medical imaging to supply chain management, and centralized management/clearing houses alongside DLT. Features: Includes theoretical concepts, empirical studies and detailed overview of various aspects related to development of healthcare applications from a reliable, trusted, and secure data transmission perspective. Provide insights on business applications of Blockchain, particularly in the healthcare sector. Explores how Blockchain can solve the transparency issues in the clinical research. Discusses AI with Blockchains, ranging from medical imaging to supply chain management. Reviews benchmark testing of AI with Blockchains and its impacts upon medical uses. This book aims at researchers and graduate students in healthcare information systems, computer and electrical engineering.

This open access book offers a detailed account of a range of mHealth initiatives across South, Southeast and East Asia. It provides readers with deep insights into the challenges such initiatives face on the ground, and a view of the diverse cultural contexts shaping strategies for overcoming these challenges. The book brings together various discussions on the broader mHealth literature, and demonstrates how a research focus on diverse Asian contexts influences the success and/or failure of current mHealth initiatives. It also highlights the important roles social scientists can play in advancing theoretical approaches, as well as planning, implementing and evaluating mHealth initiatives. The book is a valuable resource for project planners, policy developers in NGOs and government institutions, as well as academics, researchers and students in the fields of public health, communications and development studies.

Covers computational Intelligence techniques like fuzzy sets, artificial neural networks, deep neural networks, and genetic algorithm for Healthcare systems Provides easy understanding concepts like signal and image filtering techniques Includes discussion over filtering and classification problems Details studies with medical signal (ECG, EEG, EMG) and image (X-rays, FMRI, CT) datasets Describes evolution parameters such as signal-to-noise ratio, mean square error, accuracy, precision, and recall

Presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research Offers a compendium of current and emerging machine learning paradigms for healthcare informatics and reflects on the diversity and complexity through the use of case studies Provides a panoramic view of data and machine learning techniques and provides an opportunity for novel insights and discovers Explores the theory and practical applications of machine learning in healthcare Includes a guided tour of machine learning algorithms, architecture design, and applications and in interdisciplinary challenges

This book provides an insight on the importance that Internet of Things (IoT) and Information and Communication Technology (ICT) solutions can have in taking care of people's health. Key features of this book present the recent and emerging developments in various specializations in curing health problems and finding their solutions by incorporating IoT and ICT. This book presents useful IoT and ICT applications and architectures that cater to their improved healthcare requirements. Topics include in-home healthcare services based on the Internet-of-Things; RFID technology for IoT based personal healthcare; Real-time reporting and monitoring; Interfacing devices to IoT; Smart medical services; Embedded gateway configuration (EGC); Health monitoring infrastructure; and more. Features a number of practical solutions and applications of IoT and ICT on healthcare; Includes application domains such as communication technology and electronic materials and devices; Applies to researchers, academics, students, and practitioners around the world.

Explores the role of Artificial Intelligence and Smart Computing in health informatics and healthcare with an emphasis on clinical data management and analysis for precise prediction and prompt action Presents cutting edge tracking, monitoring, real time assistance, and security for IoT in healthcare Discusses broadly on wearable sensors and IoT devices and their role in smart living assistance and energy conservation Describes a system mode and architecture for a clear picture of IoT in healthcare Explains the challenges and opportunities with IoT based healthcare industries and includes a study of threats, impacts, and the need of information security

Covers the fundamentals of Machine Learning and Deep Learning in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in Machine Learning/Deep Learning models Integrates several aspects of AI-based Computational Intelligence like Machine Learning and Deep Learning from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphazises feature selection as an important step in any accurate model simulation, ML/DL methods are used to help train the system and extract the positive solution implicitly

This book describes the state of the art on computational modeling and fabrication in Tissue Engineering. It is inspired by the ECCOMAS thematic conference, the European Committee on Computational Methods in Applied Sciences, on Tissue Engineering, held in Lisbon, Portugal, June 2-4, 2011. Tissue Engineering is a multidisciplinary field involving scientists from different fields. The development of mathematical methods is quite relevant to understand cell biology and human tissues as well to model, design and fabricate optimized and smart scaffolds. Emphasis is put on mathematical and computational modeling for scaffold design and fabrication. This particular area of tissue engineering, whose goal is to obtain substitutes for hard tissues such as bone and cartilage, is growing in importance.

The current interest in developing novel materials has motivated an increasing need for biological and medical studies in a variety of dinical applications. Indeed, it is dear that to achieve the requisite mechanical, chemical and biomedical properties, especially for new bioactive materials, it is necessary to develop novel synthesis routes. The tremendous success of materials science in developing new biomaterials and fostering technological innovation arises from its focus on interdisciplinary research and collaboration between materials and medical sciences. Materials scientists seek to relate one natural phenomenon to the basic structures of the materials and to recognize the causes and effects of the phenomena. In this way, they have developed explanations for the changing of the properties, the reactions of the materials to the environment, the interface behaviors between the artificial materials and human tissue, the time effects on the materials, and many other natural occurrences. By the same means, medical scientists have also studied the biological and medical effects of these materials, and generated the knowledge needed to produce useful medical devices. The concept of biomaterials is one of the most important ideas ever generated by the application of materials science to the medical field. In traditional materials research, interest focuses primarilyon the synthesis , structure, and mechanical properties of materials commonly used for structural purposes in industry, for instance in mechanical parts of machinery.

This book presents papers from HealthyIoT 2018, the fifth edition of an international scientific event series dedicated to Internet of Things and Healthcare. The papers discuss leveraging a set of existing and emerging technologies, notions and services that can provide many solutions to delivery of electronic healthcare, patient care, and medical data management. HealthyIoT brings together technology experts, researchers, industry and international authorities contributing towards the design, development and deployment of healthcare solutions based on IoT technologies, standards, and procedures. HealthyIoT 2018 is part of the 4th annual Smart City 360 Summit, promoting multidisciplinary scientific collaboration to solve complex societal, technological and economic problems of emerging Smart Cities. The event is endorsed by the European Alliance for Innovation, an international professional community-based organisation devoted to the advancement of innovation in the field of ICT. Features practical, tested applications in IoT for healthcare; Includes application domains such as eHealth Systems, smart textiles, smart caring environments, telemedicine, wellness, and health management, etc; Applicable to researchers, academics, students, and professionals.

"This book will be a terrific introduction to the field of clinical IT and clinical informatics" -- Kevin Johnson "Dr. Braunstein has done a wonderful job of exploring a number of key trends in technology in the context of the transformations that are occurring in our health care system" -- Bob Greenes "This insightful book is a perfect primer for technologists entering the health tech field." -- Deb Estrin "This book should be read by everyone. " -- David Kibbe This book provides care providers and other non-technical readers with a broad, practical overview of the changing US healthcare system and the contemporary health informatics systems and tools that are increasingly critical to its new financial and clinical care paradigms. US healthcare delivery is dramatically transforming and informatics is at the center of the changes. Increasingly care providers must be skilled users of informatics tools to meet federal mandates and succeed under value-based contracts that demand higher quality and increased patient satisfaction but at lower cost. Yet, most have little formal training in these systems and technologies. Providers face system selection issues with little unbiased and insightful information to guide them. Patient engagement to promote wellness, prevention and improved outcomes is a requirement of Meaningful Use Stage 2 and is increasingly supported by mobile devices, apps, sensors and other technologies. Care providers need to provide guidance and advice to their patients and know how to incorporated as they generate into their care. The one-patient-at-a-time care model is being rapidly supplemented by new team-, population- and public health-based models of care. As digital data becomes ubiquitous, medicine is changing as research based on that data reveals new methods for earlier diagnosis, improved treatment and disease management and prevention. This book is clearly written, up-to-date and uses real world examples extensively to explain the tools and technologies and illustrate their practical role and potential impact on providers, patients, researchers, and society as a whole.

This book focuses on the most recent advances in the application of visualization and simulation methods to understand the flow behavior of complex fluids used in biomedical engineering and other related fields. It shows the physiological flow behavior in large arteries, microcirculation, respiratory systems and in biomedical microdevices.

This book focuses on signal processing techniques used in computational health informatics. As computational health informatics is the interdisciplinary study of the design, development, adoption and application of information and technology-based innovations, specifically, computational techniques that are relevant in health care, the book covers a comprehensive and representative range of signal processing techniques used in biomedical applications, including: bio-signal origin and dynamics, sensors used for data acquisition, artefact and noise removal techniques, feature extraction techniques in the time, frequency, time-frequency and complexity domain, and image processing techniques in different image modalities. Moreover, it includes an extensive discussion of security and privacy challenges, opportunities and future directions for computational health informatics in the big data age, and addresses the incorporation of recent techniques from the areas of artificial intelligence, deep learning and human-computer interaction. The systematic analysis of the state-of-the-art techniques covered here helps to further our understanding of the physiological processes involved and expandour capabilities in medical diagnosis and prognosis. In closing, the book, the first of its kind, blends state-of-the-art theory and practices of signal processing techniques inthe health informatics domain with real-world case studies building on those theories. As a result, it can be used as a text for health informatics courses to provide medics with cutting-edge signal processing techniques, or to introducehealth professionals who are already serving in this sector to some of the most exciting computational ideas that paved the way for the development of computational health informatics.

This book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and identification of mental states in brain computer interface (BCI) systems. The proposed methods enable the extraction of this vital information from EEG signals in order to accurately detect abnormalities revealed by the EEG. New methods will relieve the time-consuming and error-prone practices that are currently in use. Common signal processing methodologies include wavelet transformation and Fourier transformation, but these methods are not capable of managing the size of EEG data. Addressing the issue, this book examines new EEG signal analysis approaches with a combination of statistical techniques (e.g. random sampling, optimum allocation) and machine learning methods. The developed methods provide better results than the existing methods. The book also offers applications of the developed methodologies that have been tested on several real-time benchmark databases. This book concludes with thoughts on the future of the field and anticipated research challenges. It gives new direction to the field of analysis and classification of EEG signals through these more efficient methodologies. Researchers and experts will benefit from its suggested improvements to the current computer-aided based diagnostic systems for the precise analysis and management of EEG signals.

Includes innovative and new approaches for IoT in medical healthcare monitoring with 5G along with future directions Discusses the fundamental concepts and analysis of IoT and 5G in smart healthcare Focuses on methods used to apply IoT in monitoring devices for diagnosing diseases and transferring data using a 5G network. Presents new points of security and privacy concerns with expectations of IoT devices in 2030 where 91 billion devices will exist with over 10 connected devices per person Provides case studies depicting applications, best practices, as well as future predictions of IoT in everyday life Illustrates user focused wearable devices such as Fitbit health monitors and smartwatches where consumers are self-managing and self-monitoring their own health and providers are able to improve the experience of care

The Pacific Symposium on Biocomputing (PSB) 2022 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2022 will be held on January 3 - 7, 2022 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2022 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.