80 research outputs found

    Acute hearing loss

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    A corrected version of this article is available in the file named AcuteHearingLossCorrected.pdfThis issue of eMedRef provides information to clinicians on the pathophysiology, diagnosis, and therapeutics of acute hearing loss

    Multiplayer spill med EV3 mindstorm-roboter

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    Vår oppgave handler om å lage en online "Augmented reality" (AR) opplevelse der brukere kan kontrollere fysiske Lego EV3 Mindstorm roboter for å utføre virtuelle oppgaver. Robotene har blitt utstyrt med kamera foran for å la brukere observere og samhandle med det virtuelle miljøet. Bildeprosessering er brukt for å estimere posisjonen og retningen til robotene. Estimeringene er så brukt til å lage ett virtuelt miljø for å simulere en AR opplevelse.Our thesis is about creating an online augmented reality (AR) experience where users control physical Lego EV3 Mindstorm robots to perform virtual tasks. The robots are equipped with cameras in front to allow users to observe and interact with the environment. Image processing is used to estimate the position and orientation of the robots. The estimation are used with a virtual environment to simulate an AR experience

    A DOUBLE-SHRINK AUTOENCODER FOR NETWORK ANOMALY DETECTION

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    The rapid development of the Internet and the wide spread of its applications has affected many aspects of our life. However, this development also makes the cyberspace more vulnerable to various attacks. Thus, detecting and preventing these attacks are crucial for the next development of the Internet and its services. Recently, machine learning methods have been widely adopted in detecting network attacks. Among many machine learning methods, AutoEncoders (AEs) are known as the state-of-the-art techniques for network anomaly detection. Although, AEs have been successfully applied to detect many types of attacks, it is often unable to detect some difficult attacks that attempt to mimic the normal network traffic. In order to handle this issue, we propose a new model based on AutoEncoder called Double-Shrink AutoEncoder (DSAE). DSAE put more shrinkage on the normal data in the middle hidden layer. This helps to pull out some anomalies that are very similar to normal data. DSAE are evaluated on six well-known network attacks datasets. The experimental results show that our model performs competitively to the state-of-the-art model, and often out-performs this model on the attacks group that is difficult for the previous methods

    Geography of hospital admissions for multiple sclerosis in England and comparison with the geography of hospital admissions for infectious mononucleosis: a descriptive study

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    Objective It is well recognised that variation in the geographical distribution of multiple sclerosis (MS) exists. Early studies in England have shown the disease to have been more common in the North than the South. However, this could be an artefact of inaccurate diagnosis and ascertainment, and recent data on MS prevalence are lacking. In the present study, data were analysed to provide a more contemporary map of the distribution of MS in England and, as infectious mononucleosis (IM) has been shown to be associated with the risk of MS, the geographical distribution of IM with that of MS was compared.Methods Analysis of linked statistical abstracts of hospital data for England between 1999 and 2005.Results There were 56 681 MS patients. The admission rate for MS was higher in females (22/10(5); 95% CI 21.8 to 22.3) than males (10.4/10(5); 95% CI 10.2 to 10.5). The highest admission rate for MS was seen for residents of Cumbria and Lancashire (North of England) (20.1/10(5); 95% CI 19.3 to 20.8) and the lowest admission rate was for North West London residents (South of England) (12.4/10(5); 95% CI 11.8 to 13.1). The geographical distributions of IM and MS were significantly correlated (weighted regression coefficient (r (w))=0.70, p<0.0001). Admission rates for MS were lowest in the area quintile with the highest level of deprivation and they were also lowest in the area quintile with the highest percentage of population born outside the UK. A significant association between northernliness and MS remained after adjustment for deprivation and UK birthplace.Conclusions The results show the continued existence of a latitude gradient for MS in England and show a correlation with the distribution of IM. The data have implications for healthcare provision, because lifetime costs of MS exceed 1 pound million per case in the UK, as well as for studies of disease causality and prevention

    Shaping innovations in long-term care for stroke survivors with multimorbidity through stakeholder engagement

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    BACKGROUND:Stroke, like many long-term conditions, tends to be managed in isolation of its associated risk factors and multimorbidity. With increasing access to clinical and research data there is the potential to combine data from a variety of sources to inform interventions to improve healthcare. A 'Learning Health System' (LHS) is an innovative model of care which transforms integrated data into knowledge to improve healthcare. The objective of this study is to develop a process of engaging stakeholders in the use of clinical and research data to co-produce potential solutions, informed by a LHS, to improve long-term care for stroke survivors with multimorbidity. METHODS:We used a stakeholder engagement study design informed by co-production principles to engage stakeholders, including service users, carers, general practitioners and other health and social care professionals, service managers, commissioners of services, policy makers, third sector representatives and researchers. Over a 10 month period we used a range of methods including stakeholder group meetings, focus groups, nominal group techniques (priority setting and consensus building) and interviews. Qualitative data were recorded, transcribed and analysed thematically. RESULTS:37 participants took part in the study. The concept of how data might drive intervention development was difficult to convey and understand. The engagement process led to four priority areas for needs for data and information being identified by stakeholders: 1) improving continuity of care; 2) improving management of mental health consequences; 3) better access to health and social care; and 4) targeting multiple risk factors. These priorities informed preliminary design interventions. The final choice of intervention was agreed by consensus, informed by consideration of the gap in evidence and local service provision, and availability of robust data. This shaped a co-produced decision support tool to improve secondary prevention after stroke for further development. CONCLUSIONS:Stakeholder engagement to identify data-driven solutions is feasible but requires resources. While a number of potential interventions were identified, the final choice rested not just on stakeholder priorities but also on data availability. Further work is required to evaluate the impact and implementation of data-driven interventions for long-term stroke survivors

    Artificial Intelligence Model Predicts Sudden Cardiac Arrest Manifesting With Pulseless Electric Activity Versus Ventricular Fibrillation

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    BACKGROUND: There is no specific treatment for sudden cardiac arrest (SCA) manifesting as pulseless electric activity (PEA) and survival rates are low; unlike ventricular fibrillation (VF), which is treatable by defibrillation. Development of novel treatments requires fundamental clinical studies, but access to the true initial rhythm has been a limiting factor. METHODS: Using demographics and detailed clinical variables, we trained and tested an AI model (extreme gradient boosting) to differentiate PEA-SCA versus VF-SCA in a novel setting that provided the true initial rhythm. A subgroup of SCAs are witnessed by emergency medical services personnel, and because the response time is zero, the true SCA initial rhythm is recorded. The internal cohort consisted of 421 emergency medical services-witnessed out-of-hospital SCAs with PEA or VF as the initial rhythm in the Portland, Oregon metropolitan area. External validation was performed in 220 emergency medical services-witnessed SCAs from Ventura, CA. RESULTS: In the internal cohort, the artificial intelligence model achieved an area under the receiver operating characteristic curve of 0.68 (95% CI, 0.61-0.76). Model performance was similar in the external cohort, achieving an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.59-0.84). Anemia, older age, increased weight, and dyspnea as a warning symptom were the most important features of PEA-SCA; younger age, chest pain as a warning symptom and established coronary artery disease were important features associated with VF. CONCLUSIONS: The artificial intelligence model identified novel features of PEA-SCA, differentiated from VF-SCA and was successfully replicated in an external cohort. These findings enhance the mechanistic understanding of PEA-SCA with potential implications for developing novel management strategies

    Incidence of household transmission of acute gastroenteritis (AGE) in a primary care sentinel network (1992-2017): cross-sectional and retrospective cohort study protocol

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    INTRODUCTION: Acute gastroenteritis (AGE) is a highly transmissible condition. Determining characteristics of household transmission will facilitate development of prevention strategies and reduce the burden of this disease. We are carrying out this study to describe household transmission of medically attended AGE, and explore whether there is an increased incidence in households with young children. METHODS AND ANALYSIS: This study used the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) primary care sentinel network, comprising data from 1 750 167 registered patients (August 2017 database). We conducted a novel analysis using a ’household key', to identify patients within the same household (n=811 027, mean 2.16 people). A 25-year repeated cross-sectional study will explore the incidence of medically attended AGE overall and then a 5-year retrospective cohort study will describe household transmission of AGE. The cross-sectional study will include clinical data for a 25-year period—1 January 1992 until the 31 December 2017. We will describe the incidence of AGE by age-band and gender, and trends in incidence. The 5-year study will use Poisson and quasi-Poisson regression to identify characteristics of individuals and households to predict medically attended AGE transmitted in the household. This will include whether the household contained a child under 5 years and the age category of the first index case (whether adult or child under 5 years). If there is overdispersion and zero-inflation we will compare results with negative binomial to handle these issues

    Associations between exhaust and non-exhaust particulate matter and stroke incidence by stroke subtype in South London

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    Background: Airborne particulate matter (PM) consists of particles from diverse sources, including vehicle exhausts. Associations between short-term PM changes and stroke incidence have been shown. Cumulative exposures over several months, or years, are less well studied; few studies examined ischaemic subtypes or PM source. Aims: This study combines a high resolution urban air quality model with a population-based stroke register to explore associations between long-term exposure to PM and stroke incidence. Method: Data from the South London Stroke Register from 2005–2012 were included. Poisson regression explored association between stroke incidence and long-term (averaged across the study period) exposure to PM2.5(PM b 2.5 μm diameter) and PM10(PM b 10 μm), nitric oxide, nitrogen dioxide, nitrogen oxides and ozone, at the output area level (average population=309). Estimates were standardised for age and sex and adjusted for socio-economic deprivation. Models were stratified for ischaemic and haemorrhagic strokes and further broken down by Oxford Community Stroke Project classification and Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification. Results: 1800 strokes were recorded (incidence= 42.6/100,000 person-years). No associations were observed between PM and overall ischaemic or haemorrhagic incidence. For an interquartile range increase in PM2.5, there was a 23% increase in incidence (Incidence rate ratio=1.23 (95%CI: 1.03–1.44)) of total anterior circulation infarcts (TACI) and 20% increase for PM2.5 from exhausts (1.20(1.01–1.41)). Therewere similar associations with PM10, overall (1.21(1.01–1.44)) and from exhausts (1.20(1.01–1.41)). TACI incidence was not associated with non-exhaust sources. There were no associations with other stroke subtypes or pollutants. Conclusion: Outdoor air pollution, particularly that arising from vehicle exhausts, may increase risk of TACI but not other stroke subtypes

    AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: the RAVEN cohort study

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    Objectives Despite being prioritized during initial COVID-19 vaccine rollout, vulnerable individuals at high risk of severe COVID-19 (hospitalization, intensive care unit admission, or death) remain underrepresented in vaccine effectiveness (VE) studies. The RAVEN cohort study (NCT05047822) assessed AZD1222 (ChAdOx1 nCov-19) two-dose primary series VE in vulnerable populations. Methods Using the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub, linked to secondary care, death registration, and COVID-19 datasets in England, COVID-19 outcomes in 2021 were compared in vaccinated and unvaccinated individuals matched on age, sex, region, and multimorbidity. Results Over 4.5 million AZD1222 recipients were matched (mean follow-up ∼5 months); 68% were ≥50 years, 57% had high multimorbidity. Overall, high VE against severe COVID-19 was demonstrated, with lower VE observed in vulnerable populations. VE against hospitalization was higher in the lowest multimorbidity quartile (91.1%; 95% CI: 90.1, 92.0) than the highest quartile (80.4%; 79.7, 81.1), and among individuals ≥65 years, higher in the ‘fit’ (86.2%; 84.5, 87.6) than the frailest (71.8%; 69.3, 74.2). VE against hospitalization was lowest in immunosuppressed individuals (64.6%; 60.7, 68.1). Conclusions Based on integrated and comprehensive UK health data, overall population-level VE with AZD1222 was high. VEs were notably lower in vulnerable groups, particularly the immunosuppressed
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