862 research outputs found

    Prediction of Disease Using Machine Learning over Big Data-Survey

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    With massive information development in medical specialty and aid community, precise analysis of medical information advantages premature disease detection, patient care and community services. although, the analysis accuracy is reduced once the standard of medical information is incomplete. moreover, completely different regions exhibit distinctive characteristics of bound regional diseases, which can weaken the prediction of illness outbreaks. during this paper, we tend to contour machine learning algorithms for effective prediction of chronic malady eruption in disease-frequent communities. we tend to experiment the tailored prediction models over real-life hospital information collected from central China in 2013-2015. to beat the problem of incomplete information, we tend to use a latent issue model to build the missing information. we tend to experiment on a regional chronic illness of cerebral infarction. we tend to propose a replacement convolutional neural network based multimodal disease risk prediction (CNN-MDRP) algorithmic program victimisation structured and unstructured information from hospital. To the simplest of our data, none of the prevailing work targeted on each information varieties within the space of medical massive information analytics. Compared to many typical prediction algorithms, the prediction accuracy of our projected algorithmic program reaches ninety four.8% with a convergence speed that is faster than that of the CNN-based unimodal disease risk prediction (CNN-UDRP) algorithmic program

    Geospatial information infrastructures to address spatial needs in health: Collaboration, challenges and opportunities

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    Most health-related issues such as public health outbreaks and epidemiological threats are better understood from a spatial–temporal perspective and, clearly demand related geospatial datasets and services so that decision makers may jointly make informed decisions and coordinate response plans. Although current health applications support a kind of geospatial features, these are still disconnected from the wide range of geospatial services and datasets that geospatial information infrastructures may bring into health. In this paper we are questioning the hypothesis whether geospatial information infrastructures, in terms of standards-based geospatial services, technologies, and data models as operational assets already in place, can be exploited by health applications for which the geospatial dimension is of great importance. This may be certainly addressed by defining better collaboration strategies to uncover and promote geospatial assets to the health community. We discuss the value of collaboration, as well as the opportunities that geographic information infrastructures offer to address geospatial challenges in health applications

    Mapping Cloud-Edge-IoT opportunities and challenges in Europe

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    While current data processing predominantly occurs in centralized facilities, with a minor portion handled by smart objects, a shift is anticipated, with a surge in data originating from smart devices. This evolution necessitates reconfiguring the infrastructure, emphasising computing capabilities at the cloud's "edge" closer to data sources. This change symbolises the merging of cloud, edge, and IoT technologies into a unified network infrastructure - a Computing Continuum - poised to redefine tech interactions, offering novel prospects across diverse sectors. The computing continuum is emerging as a cornerstone of tech advancement in the contemporary digital era. This paper provides an in-depth exploration of the computing continuum, highlighting its potential, practical implications, and the adjustments required to tackle existing challenges. It emphasises the continuum's real-world applications, market trends, and its significance in shaping Europe's tech future

    VITASENIOR-MT: A distributed and scalable cloud-based telehealth solution

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    VITASENIOR-MT is a telehealth platform that allows to remotely monitor biometric and environmental data in a domestic environment, designed specifically to the elderly population. This paper proposes a highly scalable and efficient architecture to transport, process, store and visualize the data collected by devices of an Internet of Things (IoT) scenario. The cloud infrastructure follows a microservices architecture to provide computational scalability, better fault isolation, easy integration and automatic deployment. This solution is complemented with a pre-processing and validation of the collected data at the edge of the Internet by using the Fog Computing concept, allowing a better computing distribution. The presented approach provides personal data security and a simplified way to collect and present the data to the different actors, allowing a dynamic and intuitive management of patients and equipment to caregivers. The presented load tests proved that this solution is more efficient than a monolithic approach, promoting better access and control in the data flowing from heterogeneous equipment.This work has been financially supported by the IC&DT project VITASENIOR-MT CENTRO-01-0145- FEDER-023659 with FEDER funding through programs CENTRO2020 and FCT.info:eu-repo/semantics/publishedVersio

    Earth Observation Open Science and Innovation

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    geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

    Self-tracking modes: reflexive self-monitoring and data practices

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    The concept of ‘self-tracking’ (also referred to as life-logging, the quantified self, personal analytics and personal informatics) has recently begun to emerge in discussions of ways in which people can voluntarily monitor and record specific features of their lives, often using digital technologies. There is evidence that the personal data that are derived from individuals engaging in such reflexive self-monitoring are now beginning to be used by actors, agencies and organisations beyond the personal and privatised realm. Self-tracking rationales and sites are proliferating as part of a ‘function creep’ of the technology and ethos of self-tracking. The detail offered by these data on individuals and the growing commodification and commercial value of digital data have led government, managerial and commercial enterprises to explore ways of appropriating self-tracking for their own purposes. In some contexts people are encouraged, ‘nudged’, obliged or coerced into using digital devices to produce personal data which are then used by others. This paper examines these issues, outlining five modes of self-tracking that have emerged: private, communal, pushed, imposed and exploited. The analysis draws upon theoretical perspectives on concepts of selfhood, citizenship, biopolitics and data practices and assemblages in discussing the wider sociocultural implications of the emergence and development of these modes of self-tracking

    Technology Time Machine 2012:Paving the Path for the Future Technology Developments

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    The Digitisation of Sanitation: Transformation to Smart, Scalable and Aspirational Sanitation for All

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    In 2016 the Toilet Board Coalition ran a Feasibility Study to explore the potential role of mobile and digital applications to drive efficiencies and consumer demand in sanitation business models operating in low-income markets. The following questions were at the centre of our inquiry:- How are sanitation businesses operating in low-income markets using mobile and digital applications in their businesses today?- How are sanitation businesses and entrepreneurs thinking about next generation opportunities for mobile and digital applications for their businesses in the future?- What is needed to build the ecosystem for the digitisation of sanitation for the low income markets?Is there commercial interest and demand from large industrial operations to become buyers and investors into the system? This paper presents the findings of our study in the form of a thought piece on the topic of the digitisation of sanitation for all. Our intent is to present a number of business opportunity spaces, where we believe that value has been left on the table and customer needs unmet, to be explored further in the decade ahead.
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