77 results match your criteria: "Anglia Ruskin University Cambridge[Affiliation]"

Generative Adversarial Networks (GANs) have emerged as a powerful tool in artificial intelligence, particularly for unsupervised learning. This systematic review analyzes GAN applications in healthcare, focusing on image and signal-based studies across various clinical domains. Following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we reviewed 72 relevant journal articles.

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Article Synopsis
  • - The study examines the impact of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) on cognitive function and the importance of early detection for better management and care.
  • - It presents a systematic review of 74 research papers that focus on using deep learning and electroencephalogram (EEG) signals for detecting MCI and AD, highlighting methods for distinguishing between these conditions.
  • - The findings identify current limitations in deep learning applications for MCI and AD detection and suggest future research directions to improve early diagnosis, while also proposing high-performing models as benchmarks for subsequent studies.
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Background: Urodynamic evidence of storage dysfunction such as detrusor overactivity (DO) and/or poor compliance are present in up to 30-40% of patients after Radical Prostatectomy (RP). However, the current optimal management of men with DO on preoperative urodynamics prior to male stress urinary incontinence (SUI) surgery is not known.

Methods: We performed a systematic search of the literature including articles on patients undergoing SUI surgery after prostatectomy with preoperative DO between January 2003 and May 2023 to ensure contemporaneous data was obtained.

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Children with visual impairment (VI) are at risk of autism spectrum disorder (ASD); however standard observational diagnostic assessments are not validated for this population. The primary objective of the study is to validate a modified version of the Autism Diagnostic Observation Schedule (ADOS-2, Module 3), for children with VI. A cross-sectional observational study was undertaken with 100 (mean 5½ years, SD 10.

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Background And Aims: Increasing attention is being paid to the role of human papillomavirus (HPV) in men and specifically reproduction. Growing evidence suggests an association between HPV infection with many adverse effects including the impairment of semen parameters, the increase of blastocyst apoptosis, the reduction of endometrial implantation of trophoblastic cells, as well as the increase rate of miscarriages and spontaneous preterm birth.

Methods: We systematically searched PubMed/MEDLINE, Scopus, Embase, Web of Science, CINHAL, PsycINFO, and ERIC from inception to 2nd of July 2024, for studies that investigated the association between HPV infection with sperm parameters and fertility outcomes.

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Article Synopsis
  • Optical coherence tomography (OCT) provides high-resolution, non-invasive imaging that is crucial for diagnosing various eye diseases, including glaucoma and age-related macular degeneration, while also aiding in the detection of other conditions such as diabetic retinopathy and epiretinal membranes.
  • The systematic review followed the 2020 PRISMA guidelines, analyzing 1787 publications on eye conditions using machine learning (ML) and deep learning (DL), ultimately narrowing down to 76 relevant journal articles for in-depth study.
  • Challenges in using ML for decision support include managing numerous features and determining their relevance, whereas DL offers a more straightforward approach that doesn't require extensive trial and error.
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The status and future of essential geodiversity variables.

Philos Trans A Math Phys Eng Sci

April 2024

Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, Noord-Holland 1090 GE, The Netherlands.

Rapid environmental change, natural resource overconsumption and increasing concerns about ecological sustainability have led to the development of 'Essential Variables' (EVs). EVs are harmonized data products to inform policy and to enable effective management of natural resources by monitoring global changes. Recent years have seen the instigation of new EVs beyond those established for climate, oceans and biodiversity (ECVs, EOVs and EBVs), including Essential Geodiversity Variables (EGVs).

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Background: In the past decades, agricultural land abandonment and declining land-use intensity became common, especially in the Mediterranean countries of southern Europe. In some areas, this development opened up possibilities for rewilding and the recolonisation or expansion of large mammal populations. Yet, in some instances, co-occurrence of wild mammals and free-ranging domestic herbivores might lead to potential conflicts.

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Positron emission tomography/computed tomography (PET/CT) is increasingly used in oncology, neurology, cardiology, and emerging medical fields. The success stems from the cohesive information that hybrid PET/CT imaging offers, surpassing the capabilities of individual modalities when used in isolation for different malignancies. However, manual image interpretation requires extensive disease-specific knowledge, and it is a time-consuming aspect of physicians' daily routines.

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Causes for Retraction in the Biomedical Literature: A Systematic Review of Studies of Retraction Notices.

J Korean Med Sci

October 2023

Meta-Research Innovation Center at Stanford (METRICS) and Departments of Medicine, Epidemiology and Population Health, Biomedical Data Science, and Statistics, Stanford University, Stanford, CA, USA.

Background: Many studies have evaluated the prevalence of different reasons for retraction in samples of retraction notices. We aimed to perform a systematic review of such empirical studies of retraction causes.

Methods: The PubMed/MEDLINE database and the Embase database were searched in June 2023.

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Automated detection of airflow obstructive diseases: A systematic review of the last decade (2013-2022).

Comput Methods Programs Biomed

November 2023

School of Mathematics Physics and Computing, University of Southern Queensland, Springfield Central, QLD 4300, Australia; School of Science and Technology, Kumamoto University, Japan.

Background And Objective: Obstructive airway diseases, including asthma and Chronic Obstructive Pulmonary Disease (COPD), are two of the most common chronic respiratory health problems. Both of these conditions require health professional expertise in making a diagnosis. Hence, this process is time intensive for healthcare providers and the diagnostic quality is subject to intra- and inter- operator variability.

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Opportunity areas are primarily selected to improve the social mobility of citizens using education. This paper explores teachers' perspectives on school transitions, particularly emphasizing the role of school transition intervention activities in supporting students' resilience, behavior, academic understanding, and positive parental involvement. Informed by Multiple and Multi-dimensional Transitions (MMT) theory, the paper focuses on the outcomes of school transition intervention activities applied to new Year 7 students in a UK opportunity area.

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Automated analysis of small intestinal lamina propria to distinguish normal, Celiac Disease, and Non-Celiac Duodenitis biopsy images.

Comput Methods Programs Biomed

March 2023

School of Science and Technology, Singapore University of Social Sciences, 463 Clementi Road, 599494, Singapore; Department of Computer Engineering, Ngee Ann Polytechnic, Singapore, Singapore; Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan. Electronic address:

Article Synopsis
  • Celiac Disease (CD) is a gluten intolerance affecting genetically susceptible individuals, posing public health concerns due to its high prevalence and low diagnosis rates.
  • The study explores the use of Artificial Intelligence (AI) to analyze biopsy images of the small intestine, aiming to distinguish between normal individuals, CD patients, and those with Non-Celiac Duodenitis (NCD).
  • The AI model, specifically a Support Vector Machine (SVM), showed outstanding accuracy of 98.53% for differentiating between normal and CD, and 98.55% for distinguishing normal from NCD, marking a significant advancement in automated biopsy image analysis.
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L-Tetrolet Pattern-Based Sleep Stage Classification Model Using Balanced EEG Datasets.

Diagnostics (Basel)

October 2022

Ngee Ann Polytechnic, Department of Electronics and Computer Engineering, Singapore 599489, Singapore.

Background: Sleep stage classification is a crucial process for the diagnosis of sleep or sleep-related diseases. Currently, this process is based on manual electroencephalogram (EEG) analysis, which is resource-intensive and error-prone. Various machine learning models have been recommended to standardize and automate the analysis process to address these problems.

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Introduction: access to COVID-19 related information is fundamental to making accurate decisions and performing evidence-based actions aimed to control its spread and improve health. This study assessed pattern and perceived benefits of COVID-19 related information in Nigeria.

Methods: a descriptive cross-sectional survey was carried out among adult Nigerian residents aged 18-years and above in the geopolitical zones using multistage sampling strategy.

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Introduction: New Interventions for independence in Dementia Study (NIDUS)-Family is an Alzheimer's Society funded new manualised, multimodal psychosocial intervention to support people living with dementia (PLWD) to achieve goals that they and their family carers set, towards living as independently and as well as possible at home for longer. This process evaluation will be embedded within the NIDUS-Family Randomised Controlled Trial intervention-arm (n=199), testing how the intervention influences change, as measured by goal attainment. The evaluation will test, refine and develop the NIDUS-Family theoretical model, associated causal assumptions and logic model to identify key mechanisms of impact, implementation and contextual factors influencing the intervention's effectiveness.

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Background Low-grade inflammation in the young may contribute to the early development of cardiovascular disease. We assessed whether circulating levels of glycoprotein acetyls (GlycA) were better able to predict the development of adverse cardiovascular disease risk profiles compared with the more commonly used biomarker high-sensitivity CRP (C-reactive protein). Methods and Results A total of 3306 adolescents and young adults from the Avon Longitudinal Study of Parents and Children (mean age, 15.

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Article Synopsis
  • - This study investigates the link between back and neck pain (BNP) and absenteeism from work, using data from a large US population sample collected in 2019.
  • - The analysis showed that BNP significantly contributes to higher rates of absenteeism, with difficulties in walking, standing, and sitting accounting for a substantial part of this relationship.
  • - The findings suggest that workplace interventions, like exercise and ergonomic improvements, can help manage BNP and reduce absenteeism.
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Antimicrobial resistance (AMR) has been detected in the microbiota of wildlife, yet little is known about the origin and impact within the ecosystem. Due to the shortage of nonepizootic surveillance, there is limited understanding of the natural prevalence and circulation of AMR bacteria in the wild animal population, including avian species. In this surveillance study, feces from wild birds in proximity to the River Cam, Cambridge, England, were collected and spp.

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Association between diabetes and edentulism and their joint effects on health status in 40 low and middle-income countries.

BMJ Open Diabetes Res Care

October 2021

Research and Development Unit, Parc Sanitari Sant Joan de Deu, Sant Boi de Llobregat, Spain.

Introduction: Previous studies on the diabetes-edentulism relationship have yielded conflicting results. Therefore, the goal of this study was to investigate the association between diabetes and edentulism, and their joint effects on health status in adults from 40 low and middle-income countries (LMICs).

Research Design And Methods: Data from the World Health Survey were used for this cross-sectional study (2002-2004).

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Core and occasional species: A new way forward.

Ecol Evol

August 2021

Applied Ecology Research Group School of Life Sciences, Anglia Ruskin University Cambridge UK.

Various methods have been used to divide communities into core species and occasional or satellite species. Some methods are somewhat arbitrary, and there is evidence that many communities are more multimodal than bimodal. They also tend to rely on having multiple years of data.

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Objective: To systematically review all published and unpublished evidence on the impact of the COVID-19 pandemic on the health and well-being of UK sexual and gender minority (LGBT+; lesbian, gay, bisexual, transgender, non-binary, intersex and queer) people.

Methods: Any relevant studies with or without comparator were included, with outcomes of: COVID-19 incidence, hospitalisation rates, illness severity, death rates, other health and well-being. Six databases (platforms) were searched-CINAHL Plus (Ovid), Cochrane Central (Cochrane Library), Medline (Ovid), Embase (Ovid), Science Citation Index (Web of Science) and Scopus between 2019 and 2020 in December 2020, using synonyms for sexual and gender minorities and COVID-19 search terms.

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Sarcopenia and Mild Cognitive Impairment in Older Adults from Six Low- and Middle-Income Countries.

J Alzheimers Dis

November 2021

Research and Development Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Barcelona, Spain.

Background: Little is known about the relationship between sarcopenia and mild cognitive impairment (MCI) in low- and middle-income countries (LMICs).

Objective: This study aimed to investigate this association among community-dwelling adults aged≥65 years from six LMICs.

Methods: Cross-sectional, nationally representative data from the Study on Global Ageing and Adult Health (SAGE) were analyzed.

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Objective: In March 2020, several countries banned unnecessary outdoor activities during COVID-19, commonly called 'lockdowns. These lockdowns have the potential to impact associated levels of physical activity and sedentary behaviour. Given the numerous health outcomes associated with physical activity and sedentary behaviour, the aim of this review was to summarise literature that investigated differences in physical activity and sedentary behaviour before vs during the COVID-19 lockdown.

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