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Articles 1 - 13 of 13
Full-Text Articles in Medicine and Health Sciences
Supporting Compliance Of Occupational Safety And Health Requirements - European Labour Inspection Systems Of Sanctions And Standardised Measures, Victor Hrymak
Articles
European legislation for occupational safety and health (OSH) is based on the prevention of accidents and ill health. Apart from European directives, all Member States have national laws and strategies and expect enterprises to implement this preventative ethos, and thereby ensure adequate performance in OSH. Labour Inspectorates monitor and if necessary enforce these laws by deploying individual Labour Inspectors to chosen enterprises. If workplace safety and health conditions are found to be substandard, Labour Inspectors are expected to improve the situation using persuasion and, if necessary, their authority to compel enterprises through specific sanction powers. Bruhn (2009) describes this interaction …
Current Topics In Technology-Enabled Stroke Rehabilitation And Reintegration: A Scoping Review And Content Analysis, Katryna Cisek
Current Topics In Technology-Enabled Stroke Rehabilitation And Reintegration: A Scoping Review And Content Analysis, Katryna Cisek
Articles
Background. There is a worldwide health crisis stemming from the rising incidence of various debilitating chronic diseases, with stroke as a leading contributor. Chronic stroke management encompasses rehabilitation and reintegration, and can require decades of personalized medicine and care. Information technology (IT) tools have the potential to support individuals managing chronic stroke symptoms. Objectives. This scoping review identifies prevalent topics and concepts in research literature on IT technology for stroke rehabilitation and reintegration, utilizing content analysis, based on topic modelling techniques from natural language processing to identify gaps in this literature. Eligibility Criteria. Our methodological search initially identified over 14,000 …
Walkable Neighborhoods: Linkages Between Place, Health, And Happiness In Younger And Older Adults, Kevin M. Leyden, Michael J. Hogan, Lorraine D'Arcy, Brendan Bunting, Sebastiaan Bierema
Walkable Neighborhoods: Linkages Between Place, Health, And Happiness In Younger And Older Adults, Kevin M. Leyden, Michael J. Hogan, Lorraine D'Arcy, Brendan Bunting, Sebastiaan Bierema
Articles
Problem, research strategy, and findings: We examined whether living in a walkable neighborhood influenced the happiness of younger and older city residents. The data for this study came from a comprehensive household population survey of 1,064 adults living in 16 neighborhoods in Dublin City (Ireland) and its suburbs. We used multigroup structural equation modeling to analyze the direct and indirect effects of walkability on happiness, mediated by health, trust, and satisfaction with neighborhood appearance. We found living in a walkable neighborhood was directly linked to the happiness of people aged 36 to 45 (p¼.001) and, to a lesser extent, those …
The Future Of Clinical Trials Of Myopia Control, Mark A. Bullimore, Noel A. Brennan, Daniel I. Flintcroft
The Future Of Clinical Trials Of Myopia Control, Mark A. Bullimore, Noel A. Brennan, Daniel I. Flintcroft
Articles
In the field of myopia control, effective optical or pharmaceutical therapies are now available to patients in many markets. This creates challenges for the conduct of placebo-controlled, randomised clinical trials, including ethics, recruitment, retention, selective loss of faster progressors and non-protocol treatments: 1. Ethics: It is valid to question whether withholding treatment in control subjects is ethical. 2. Recruitment: Availability of treatments is making recruitment into clinical trials more difficult. 3. Retention: If masking is not possible, parents may immediately withdraw their child if randomised to no treatment. 4. Selective loss: Withdrawal of fast progressors in the control group leading …
Monitoring And Modelling The Glutamine Metabolic Pathway: A Review And Future Perspectives, Zohreh Mirveis, Paul Cahill, Nitin Patel, Hugh Byrne
Monitoring And Modelling The Glutamine Metabolic Pathway: A Review And Future Perspectives, Zohreh Mirveis, Paul Cahill, Nitin Patel, Hugh Byrne
Articles
In this review, the contribution of NMR to the metabolomics field will be discussed—particularly as it relates to cancer and drug metabolism research. An overview of the typical NMR metabolomic experiment will be presented while emphasizing important caveats ranging from experimental design to data interpretation.
Machine-Learning-Based Head Impact Subtyping Based On The Spectral Densities Of The Measurable Head Kinematics, Xianghao Zhan, Yiheng Li, Yuzhe Liu, Nicholas J. Cecchi, Samuel J. Raymond, Zhou Zhou, Hossein Vahid Alizadeh, Jesse Ruan, Saeed Barbat, Stephen Tiernan, Olivier Gevaert, Michael M. Zeineh, Gerald A. Grant, David B. Camarillo
Machine-Learning-Based Head Impact Subtyping Based On The Spectral Densities Of The Measurable Head Kinematics, Xianghao Zhan, Yiheng Li, Yuzhe Liu, Nicholas J. Cecchi, Samuel J. Raymond, Zhou Zhou, Hossein Vahid Alizadeh, Jesse Ruan, Saeed Barbat, Stephen Tiernan, Olivier Gevaert, Michael M. Zeineh, Gerald A. Grant, David B. Camarillo
Articles
Traumatic brain injury can be caused by head impacts, but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo and the characteristics of different types of impacts are not well studied. We investigated the spectral characteristics of different head impact types with kinematics classification. Methods: Data was analyzed from 3,262 head impacts from lab reconstruction, American football, mixed martial arts, and publicly available car crash data. A random forest classifier with spectral densities of linear acceleration and angular velocity was built to classify head impact types (e.g., football, car crash, …
Understanding And Predicting Cognitive Improvement Of Young Adults In Ischemic Stroke Rehabilitation Therapy, Helard Becerra Martinez, Katryna Cisek, Alejandro Garcia-Rudolph, John Kelleher, Andrew Hines
Understanding And Predicting Cognitive Improvement Of Young Adults In Ischemic Stroke Rehabilitation Therapy, Helard Becerra Martinez, Katryna Cisek, Alejandro Garcia-Rudolph, John Kelleher, Andrew Hines
Articles
Accurate early predictions of a patient's likely cognitive improvement as a result of a stroke rehabilitation programme can assist clinicians in assembling more effective therapeutic programs. In addition, sufficient levels of explainability, which can justify these predictions, are a crucial requirement, as reported by clinicians. This article presents a machine learning (ML) prediction model targeting cognitive improvement after therapy for stroke surviving patients. The prediction model relies on electronic health records from 201 ischemic stroke surviving patients containing demographic information, cognitive assessments at admission from 24 different standardized neuropsychology tests (e.g., TMT, WAIS-III, Stroop, RAVLT, etc.), and therapy information collected …
Portable Hepa Filtration Successfully Augments Natural-Ventilation-Mediated Airborne Particle Clearance In A Legacy Design Hospital Ward, Mehael Fennelly, S. Hellebust, J. Wenger, D. O'Connor, G.W. Griffith, B.J. Plant, A.P.C. Microbiome Institute
Portable Hepa Filtration Successfully Augments Natural-Ventilation-Mediated Airborne Particle Clearance In A Legacy Design Hospital Ward, Mehael Fennelly, S. Hellebust, J. Wenger, D. O'Connor, G.W. Griffith, B.J. Plant, A.P.C. Microbiome Institute
Articles
As the severe acute respiratory syndrome coronavirus-2 pandemic has proceeded, ventilation has been recognized increasingly as an important tool in infection control. Many hospitals in Ireland and the UK do not have mechanical ventilation and depend on natural ventilation. The effectiveness of natural ventilation varies with atmospheric conditions and building design. In a challenge test of a legacy design ward, this study showed that portable air filtration significantly increased the clearance of pollutant aerosols of respirable size compared with natural ventilation, and reduced spatial variation in particle persistence. A combination of natural ventilation and portable air filtration is significantly more …
Forecasting Covid-19 Cases Using Dynamic Time Warping And Incremental Machine Learning Methods, Luis Miralles-Pechuán, Ankit Kumar, Andres L. Suarez-Cetrulo
Forecasting Covid-19 Cases Using Dynamic Time Warping And Incremental Machine Learning Methods, Luis Miralles-Pechuán, Ankit Kumar, Andres L. Suarez-Cetrulo
Articles
The investment of time and resources for developing better strategies is key to dealing with future pandemics. In this work, we recreated the situation of COVID-19 across the year 2020, when the pandemic started spreading worldwide. We conducted experiments to predict the coronavirus cases for the 50 countries with the most cases during 2020. We compared the performance of state-of-the-art machine learning algorithms, such as long-short-term memory networks, against that of online incremental machine learning algorithms. To find the best strategy, we performed experiments to test three different approaches. In the first approach (single-country), we trained each model using data …
Exploring The Impact Of Noise And Degradations On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever
Exploring The Impact Of Noise And Degradations On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever
Articles
The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart sound signals need to be captured using a signal acquisition device. However, it is almost impossible to capture noise-free heart sound signals due to the presence of internal and external noises in most situations. Such noises and degradations in heart sound signals can potentially reduce the accuracy of data-driven classification models. Although different techniques have been proposed in the literature to address the noise issue, how and to what extent different noise …
Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed
Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed
Articles
The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that …
Assessing The Impact Of Contact Tracing With An Agent-Based Model For Simulating The Spread Of Covid-19: The Irish Experience, Elizabeth Hunter, Sudipta Saha, Jwenish Kumawat, Ciara Carroll, John Kelleher, Claire Buckley, Conor Mcaloon, Patricia Kearney, Michelle Gilbert, Greg Martin
Assessing The Impact Of Contact Tracing With An Agent-Based Model For Simulating The Spread Of Covid-19: The Irish Experience, Elizabeth Hunter, Sudipta Saha, Jwenish Kumawat, Ciara Carroll, John Kelleher, Claire Buckley, Conor Mcaloon, Patricia Kearney, Michelle Gilbert, Greg Martin
Articles
Contact tracing is an important tool in managing infectious disease outbreaks and Ireland used a comprehensive contact tracing program to slow the spread of COVID-19. Although the benefits of contact tracing seem obvious, it is difficult to estimate the actual impact contact tracing has on an outbreak because it is hard to separate the effects of contact tracing from other behavioural changes or interventions. To understand the impact contact tracing had in Ireland, we used an agent-based model that is designed to simulate the spread of COVID-19 through Ireland. The model uses real contact tracing data from the first year …
Enhancing The Prediction For Shunt‑Dependent Hydrocephalus After Aneurysmal Subarachnoid Hemorrhage Using A Machine Learning Approach, Dietmar Frey, Adam Hilbert, Anton Früh, Vince Istvan Madai, Tabea Kossen, Julia Kiewitz, Jenny Sommerfeld, Peter Vajkoczy, Meike Unteroberdörster, Esra Zihni, Sophie Charlotte Brune, Stefan Wolf, Nora Franziska Dengler
Enhancing The Prediction For Shunt‑Dependent Hydrocephalus After Aneurysmal Subarachnoid Hemorrhage Using A Machine Learning Approach, Dietmar Frey, Adam Hilbert, Anton Früh, Vince Istvan Madai, Tabea Kossen, Julia Kiewitz, Jenny Sommerfeld, Peter Vajkoczy, Meike Unteroberdörster, Esra Zihni, Sophie Charlotte Brune, Stefan Wolf, Nora Franziska Dengler
Articles
Early and reliable prediction of shunt-dependent hydrocephalus (SDHC) after aneurysmal subarachnoid haemorhage (a SAH) may decrease the duration of in-hospital stay and reduce the risk of catheter-associated meningitis. Machine learning (ML) may improve predictions of SDHC in comparison to traditional non-ML methods. ML models were trained for CHESS and SDASH and two combined individual feature sets with clinical, radiographic, and laboratory variables. Seven different algorithms were used including three types of generalized linear models (GLM) as well as a tree boosting (Cat Boost) algorithm, a Nave Bayes (NB) classifier, and a multilayer perceptron (MLP) artificial neural net. The discrimination of …