Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

European Language Grid

This open access book provides an in-depth description of the EU project European Language Grid (ELG). Its motivation lies in the fact that Europe is a multilingual society with 24 official European Union Member State languages and dozens of additional languages including regional and minority languages. The only meaningful way to enable multilingualism and to benefit from this rich linguistic heritage is through Language Technologies (LT) including Natural Language Processing (NLP), Natural Language Understanding (NLU), Speech Technologies and language-centric Artificial Intelligence (AI) applications. The European Language Grid provides a single umbrella platform for the European LT community, including research and industry, effectively functioning as a virtual home, marketplace, showroom, and deployment centre for all services, tools, resources, products and organisations active in the field. Today the ELG cloud platform already offers access to more than 13,000 language processing tools and language resources. It enables all stakeholders to deposit, upload and deploy their technologies and datasets. The platform also supports the long-term objective of establishing digital language equality in Europe by 2030 – to create a situation in which all European languages enjoy equal technological support. This is the very first book dedicated to Language Technology and NLP platforms. Cloud technology has only recently matured enough to make the development of a platform like ELG feasible on a larger scale. The book comprehensively describes the results of the ELG project. Following an introduction, the content is divided into four main parts: (I) ELG Cloud Platform; (II) ELG Inventory of Technologies and Resources; (III) ELG Community and Initiative; and (IV) ELG Open Calls and Pilot Projects

Deep Learning in Medical Image Analysis

The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

European Language Grid

This open access book provides an in-depth description of the EU project European Language Grid (ELG). Its motivation lies in the fact that Europe is a multilingual society with 24 official European Union Member State languages and dozens of additional languages including regional and minority languages. The only meaningful way to enable multilingualism and to benefit from this rich linguistic heritage is through Language Technologies (LT) including Natural Language Processing (NLP), Natural Language Understanding (NLU), Speech Technologies and language-centric Artificial Intelligence (AI) applications. The European Language Grid provides a single umbrella platform for the European LT community, including research and industry, effectively functioning as a virtual home, marketplace, showroom, and deployment centre for all services, tools, resources, products and organisations active in the field. Today the ELG cloud platform already offers access to more than 13,000 language processing tools and language resources. It enables all stakeholders to deposit, upload and deploy their technologies and datasets. The platform also supports the long-term objective of establishing digital language equality in Europe by 2030 – to create a situation in which all European languages enjoy equal technological support. This is the very first book dedicated to Language Technology and NLP platforms. Cloud technology has only recently matured enough to make the development of a platform like ELG feasible on a larger scale. The book comprehensively describes the results of the ELG project. Following an introduction, the content is divided into four main parts: (I) ELG Cloud Platform; (II) ELG Inventory of Technologies and Resources; (III) ELG Community and Initiative; and (IV) ELG Open Calls and Pilot Projects

Sensing and Signal Processing in Smart Healthcare

In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human–computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included

Digital Transformation in Healthcare

This book presents a collection of papers revealing the impact of advanced computation and instrumentation on healthcare. It highlights the increasing global trend driving innovation for a new era of multifunctional technologies for personalized digital healthcare. Moreover, it highlights that contemporary research on healthcare is performed on a multidisciplinary basis comprising computational engineering, biomedicine, biomedical engineering, electronic engineering, and automation engineering, among other areas

Interaction analytics for automatic assessment of communication quality in primary care

Effective doctor-patient communication is a crucial element of health care, influencing patients’ personal and medical outcomes following the interview. The set of skills used in interpersonal interaction is complex, involving verbal and non-verbal behaviour. Precise attributes of good non-verbal behaviour are difficult to characterise, but models and studies offer insight on relevant factors. In this PhD, I studied how the attributes of non-verbal behaviour can be automatically extracted and assessed, focusing on turn-taking patterns of and the prosody of patient-clinician dialogues. I described clinician-patient communication and the tools and methods used to train and assess communication during the consultation. I then proceeded to a review of the literature on the existing efforts to automate assessment, depicting an emerging domain focused on the semantic content of the exchange and a lack of investigation on interaction dynamics, notably on the structure of turns and prosody. To undertake the study of these aspects, I initially planned the collection of data. I underlined the need for a system that follows the requirements of sensitive data collection regarding data quality and security. I went on to design a secure system which records participants’ speech as well as the body posture of the clinician. I provided an open-source implementation and I supported its use by the scientific community. I investigated the automatic extraction and analysis of some non-verbal components of the clinician-patient communication on an existing corpus of GP consultations. I outlined different patterns in the clinician-patient interaction and I further developed explanations of known consulting behaviours, such as the general imbalance of the doctor-patient interaction and differences in the control of the conversation. I compared behaviours present in face to face, telephone, and video consultations, finding overall similarities alongside noticeable differences in patterns of overlapping speech and switching behaviour. I further studied non-verbal signals by analysing speech prosodic features, investigating differences in participants’ behaviour and relations between the assessment of the clinician-patient communication and prosodic features. While limited in their interpretative power on the explored dataset, these signals nonetheless provide additional metrics to identify and characterise variations in the non-verbal behaviour of the participants. Analysing clinician-patient communication is difficult even for human experts. Automating that process in this work has been particularly challenging. I demonstrated the capacity of automated processing of non-verbal behaviours to analyse clinician-patient communication. I outlined the ability to explore new aspects, interaction dynamics, and objectively describe how patients and clinicians interact. I further explained known aspects such as clinician dominance in more detail. I also provided a methodology to characterise participants’ turns taking behaviour and speech prosody for the objective appraisal of the quality of non-verbal communication. This methodology is aimed at further use in research and education