9,797 research outputs found
Batch and Streaming Data Ingestion towards Creating Holistic Health Records
The healthcare sector has been moving toward Electronic Health Record (EHR) systems that produce enormous amounts of healthcare data due to the increased emphasis on getting the appropriate information to the right person, wherever they are, at any time. This highlights the need for a holistic approach to ingest, exploit, and manage these huge amounts of data for achieving better health management and promotion in general. This manuscript proposes such an approach, providing a mechanism allowing all health ecosystem entities to obtain actionable knowledge from heterogeneous data in a multimodal way. The mechanism includes diverse techniques for automatically ingesting healthcare-related information from heterogeneous sources that produce batch/streaming data, managing, fusing, and aggregating this data into new data structures (i.e., Holistic Health Records (HHRs)). The latter enable the aggregation of data coming from different sources, such as Internet of Medical Things (IoMT) devices, online/offline platforms, while to effectively construct the HHRs, the mechanism develops various data management techniques covering the overall data path, from data acquisition and cleaning to data integration, modelling, and interpretation. The mechanism has been evaluated upon different healthcare scenarios, ranging from hospital-retrieved data to patient platforms, combined with data obtained from IoMT devices, having produced useful insights towards its successful and wide adaptation in this domain. In order to implement a paradigm shift from heterogeneous and independent data sources, limited data exploitation, and health records, the mechanism has combined multidisciplinary technologies toward HHRs. Doi: 10.28991/ESJ-2023-07-02-03 Full Text: PD
Healthcare 4.0: Trends, Challenges and Benefits
The Fourth Industry Revolution, known as Industry 4.0, refers to the forces that are transforming industry, including the healthcare industry, where it has been termed Healthcare 4.0. Though lagging other industries in the adoption of new innovative technologies, the healthcare industry is embracing the potential benefits that arise from new innovative technologies. New trends revealed both in the academic literature and by industry practice show that researchers and practitioners are becoming more aware of the benefits technology can bring to an industry as complex as the healthcare industry. The object of the study is to identify the challenges, trends and gaps in the existing body of research with regard to Healthcare 4.0. In this study, a systematic literature review on Healthcare 4.0 research papers was conducted to identify trends, challenges and the perceived benefits that may arise from it. This paper found that there is a need to conduct more empirical studies in this area. It, further, identified the need to implement practical procedures in the industry to get feedback from patients and healthcare participants in order to promote the adoption of new Healthcare 4.0 technologie
The Impact of the Global Financial Crisis on Education and Healthcare in the Economies of the Former Soviet Union – the Case of Moldova
This study reviews the impact of the global financial crisis on public service delivery in the Republic of Moldova. It provides a background of the country’s development in the period prior to the crisis (2000 to 2007/2008) and presents the factors which determined the country’s fiscal performance during the crisis (2008-2010). The main aim of the study is to describe the changes in education and health financing and the associated changes in service delivery during the crisis. The presentation of the reforms in the social sector is necessary to set the stage for discussion and is not a primary goal of this study. In particular, the study analyzes the size and dynamics of public financing of education and healthcare and their intra-sector structure, as well as crisis management. It measures the impact the financial crisis had on the quality and reliability of public services and analyzes policy measures undertaken by the government to mitigate crisis’ impact. Conclusions and recommendations derived from the study should enable national policy-makers and international institutions supporting public finance reforms to improve the targeting of limited public resources both between and within individual sectors.Economic Crisis, Economic Development, Fiscal Policy, Education, Healthcare
A Survey of Multimodal Information Fusion for Smart Healthcare: Mapping the Journey from Data to Wisdom
Multimodal medical data fusion has emerged as a transformative approach in
smart healthcare, enabling a comprehensive understanding of patient health and
personalized treatment plans. In this paper, a journey from data to information
to knowledge to wisdom (DIKW) is explored through multimodal fusion for smart
healthcare. We present a comprehensive review of multimodal medical data fusion
focused on the integration of various data modalities. The review explores
different approaches such as feature selection, rule-based systems, machine
learning, deep learning, and natural language processing, for fusing and
analyzing multimodal data. This paper also highlights the challenges associated
with multimodal fusion in healthcare. By synthesizing the reviewed frameworks
and theories, it proposes a generic framework for multimodal medical data
fusion that aligns with the DIKW model. Moreover, it discusses future
directions related to the four pillars of healthcare: Predictive, Preventive,
Personalized, and Participatory approaches. The components of the comprehensive
survey presented in this paper form the foundation for more successful
implementation of multimodal fusion in smart healthcare. Our findings can guide
researchers and practitioners in leveraging the power of multimodal fusion with
the state-of-the-art approaches to revolutionize healthcare and improve patient
outcomes.Comment: This work has been submitted to the ELSEVIER for possible
publication. Copyright may be transferred without notice, after which this
version may no longer be accessibl
Revisiting the Internet of Things: New Trends, Opportunities and Grand Challenges
The Internet of Things (IoT) has brought the dream of ubiquitous data access
from physical environments into reality. IoT embeds sensors and actuators in
physical objects so that they can communicate and exchange data between
themselves to improve efficiency along with enabling real-time intelligent
services and offering better quality of life to people. The number of deployed
IoT devices has rapidly grown in the past five years in a way that makes IoT
the most disruptive technology in recent history. In this paper, we reevaluate
the position of IoT in our life and provide deep insights on its enabling
technologies, applications, rising trends and grand challenges. The paper also
highlights the role of artificial intelligence to make IoT the top
transformative technology that has been ever developed in human history
The disease of corruption: views on how to fight corruption to advance 21st century global health goals
Corruption has been described as a disease. When corruption infiltrates global health, it can be particularly devastating, threatening hard gained improvements in human and economic development, international security, and population health. Yet, the multifaceted and complex nature of global health corruption makes it extremely difficult to tackle, despite its enormous costs, which have been estimated in the billions of dollars. In this forum article, we asked anti-corruption experts to identify key priority areas that urgently need global attention in order to advance the fight against global health corruption. The views shared by this multidisciplinary group of contributors reveal several fundamental challenges and allow us to explore potential solutions to address the unique risks posed by health-related corruption. Collectively, these perspectives also provide a roadmap that can be used in support of global health anti-corruption efforts in the post-2015 development agenda
Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine
Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.11Ysciescopu
Join operation for semantic data enrichment of asynchronous time series data
In this paper, we present a novel framework for enriching time series data in smart cities by supplementing it with information from external sources via semantic data enrichment. Our methodology effectively merges multiple data sources into a uniform time series, while addressing difficulties such as data quality, contextual information, and time lapses. We demonstrate the efficacy of our method through a case study in Barcelona, which permitted the use of advanced analysis methods such as windowed cross-correlation and peak picking. The resulting time series data can be used to determine traffic patterns and has potential uses in other smart city sectors, such as air quality, energy efficiency, and public safety. Interactive dashboards enable stakeholders to visualize and summarize key insights and patterns.Postprint (published version
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