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Full-Text Articles in Computer Engineering

Current Topics In Technology-Enabled Stroke Rehabilitation And Reintegration: A Scoping Review And Content Analysis, Katryna Cisek Jan 2023

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 …


Medical Concept Mention Identification In Social Media Posts Using A Small Number Of Sample References, Vasudevan Nedumpozhimana, Sneha Rautmare, Meegan Gower, Maja Popovic, Nishtha Jain, Patricia Buffini, John Kelleher Jan 2023

Medical Concept Mention Identification In Social Media Posts Using A Small Number Of Sample References, Vasudevan Nedumpozhimana, Sneha Rautmare, Meegan Gower, Maja Popovic, Nishtha Jain, Patricia Buffini, John Kelleher

Conference papers

Identification of mentions of medical concepts in social media text can provide useful information for caseload prediction of diseases like Covid-19 and Measles. We propose a simple model for the automatic identification of the medical concept mentions in the social media text. We validate the effectiveness of the proposed model on Twitter, Reddit, and News/Media datasets.


Exploring The Impact Of Noise And Degradations On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever Jan 2023

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 …


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 Jan 2023

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 …


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 Jan 2023

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 …


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 Jan 2023

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 …


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 Jan 2023

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 …


Forecasting Covid-19 Cases Using Dynamic Time Warping And Incremental Machine Learning Methods, Luis Miralles-Pechuán, Ankit Kumar, Andres L. Suarez-Cetrulo Jan 2023

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 Concept Of The Digital Educator During Covid-19, Fernando Jimenez, Gracia Sanchez, Jose Palma, Luis Miralles-Pechuán, Juan A. Botia Jan 2022

Exploring The Concept Of The Digital Educator During Covid-19, Fernando Jimenez, Gracia Sanchez, Jose Palma, Luis Miralles-Pechuán, Juan A. Botia

Articles

T In many machine learning classification problems, datasets are usually of high dimensionality and therefore require efficient and effective methods for identifying the relative importance of their attributes, eliminating the redundant and irrelevant ones. Due to the huge size of the search space of the possible solutions, the attribute subset evaluation feature selection methods are not very suitable, so in these scenarios feature ranking methods are used. Most of the feature ranking methods described in the literature are univariate methods, which do not detect interactions between factors. In this paper, we propose two new multivariate feature ranking methods based on …


The Association Between Ambient Uvb Dose And Anca‑Associated Vasculitis Relapse And Onset, Jennifer Scott, Enock Havyarimana, Albert Navarro-Gallinad, Arthur White, Jason Wyse, Jos Van Geffen, Michiel Van Weele, Antonia Buettner, Tamara Wanigasekera, Cathal Walsh, Louis Aslett, John Kelleher, Julie Power, James Ng, Declan O’Sullivan, Lucy Hederman, Neil Basu, Mark A. Little, Lina Zgaga Jan 2022

The Association Between Ambient Uvb Dose And Anca‑Associated Vasculitis Relapse And Onset, Jennifer Scott, Enock Havyarimana, Albert Navarro-Gallinad, Arthur White, Jason Wyse, Jos Van Geffen, Michiel Van Weele, Antonia Buettner, Tamara Wanigasekera, Cathal Walsh, Louis Aslett, John Kelleher, Julie Power, James Ng, Declan O’Sullivan, Lucy Hederman, Neil Basu, Mark A. Little, Lina Zgaga

Articles

The aetiology of ANCA-associated vasculitis (AAV) and triggers of relapse are poorly understood. Vitamin D (vitD) is an important immunomodulator, potentially responsible for the observed latitudinal differences between granulomatous and non-granulomatous AAV phenotypes. A narrow ultraviolet B spectrum induces vitD synthesis (vitD-UVB) via the skin. We hypothesised that prolonged periods of low ambient UVB (and by extension vitD deficiency) are associated with the granulomatous form of the disease and an increased risk of AAV relapse.


A Hybrid Agent-Based And Equation Based Epidemiological Model For The Spread Of Infectious Diseases, Elizabeth Hunter Feb 2020

A Hybrid Agent-Based And Equation Based Epidemiological Model For The Spread Of Infectious Diseases, Elizabeth Hunter

Doctoral

Infectious disease models are essential in understanding how an outbreak might occur and how best to mitigate an outbreak. One of the most important factors in modelling a disease is choosing an appropriate model and determining the assump tions needed to create the model. The main research questions this thesis addresses are how do we create a model for the spread of infectious diseases that captures heterogeneous agents without using an inordinate amount of computing power and how can we use that model to plan for future infectious disease outbreaks. We start our work by analysing and comparing equation based …


Intelligibility Of Electrolarynx Speech Using A Novel Hands-Free Actuator, Brian Madden, Mark Nolan, Ted Burke, James Condron, Eugene Coyle Jan 2011

Intelligibility Of Electrolarynx Speech Using A Novel Hands-Free Actuator, Brian Madden, Mark Nolan, Ted Burke, James Condron, Eugene Coyle

Conference Papers

During voiced speech, the larynx provides quasi-periodic acoustic excitation of the vocal tract. In most electrolarynxes, mechanical vibrations are produced by a linear electromechanical actuator, the armature of which percusses against a metal or plastic plate at a frequency within the range of glottal excitation. In this paper, the intelligibility of speech produced using a novel hands-free actuator is compared to speech produced using a conventional electrolarynx. Two able-bodied speakers (one male, one female) performed a closed response test containing 28 monosyllabic words, once using a conventional electrolarynx and a second time using the novel design. The resulting audio recordings …


Augmented Control Of A Hands-Free Electrolarynx, Brian Madden, James Condron, Eugene Coyle Jan 2011

Augmented Control Of A Hands-Free Electrolarynx, Brian Madden, James Condron, Eugene Coyle

Conference Papers

During voiced speech, the larynx acts as the sound source, providing a quasi-periodic excitation of the vocal tract. Following a total laryngectomy, some people speak using an electrolarynx which employs an electromechanical actuator to perform the excitatory function of the absent larynx. Drawbacks of conventional electrolarynx designs include the monotonic sound emitted, the need for a free-hand to operate the device, and the difficulty experienced by many laryngectomees in adapting to its use. One improvement to the electrolarynx, which clinicians and users frequently suggest, is the provision of a convenient hands-free control facility. This would allow more natural use of …


Attitudes Of Health Professionals To Electronic Data Sharing Within An Integrated Care Electronic Health Record (Icehr), Charyl O'Malley, Damon Berry, Mary Sharp Nov 2010

Attitudes Of Health Professionals To Electronic Data Sharing Within An Integrated Care Electronic Health Record (Icehr), Charyl O'Malley, Damon Berry, Mary Sharp

Conference Papers

It is estimated that 98,000 people die in hospitals yearly in the USA as a result of medical errors (Agency for Healthcare Research and Quality, 2009). Electronic Health Records (EHR) can offer improved patient safety. EHRs are being implemented by many countries, however, not all health professionals have welcomed them (MORI Social Research Institute, 2006). As outlined in the National Health Information Strategy (NHIS) document, Ireland has plans to introduce an EHR. Attitudes of health professionals are a significant factor for the successful implementation and adoption of a new clinical information system. This study aimed to gauge the attitude of …


Authentication Of Biometric Features Using Texture Coding For Id Cards, Jonathan Blackledge, Eugene Coyle Jan 2010

Authentication Of Biometric Features Using Texture Coding For Id Cards, Jonathan Blackledge, Eugene Coyle

Conference papers

The use of image based information exchange has grown rapidly over the years in terms of both e-to-e image storage and transmission and in terms of maintaining paper documents in electronic form. Further, with the dramatic improvements in the quality of COTS (Commercial-Off-The-Shelf) printing and scanning devices, the ability to counterfeit electronic and printed documents has become a widespread problem. Consequently, there has been an increasing demand to develop digital watermarking techniques which can be applied to both electronic and printed images (and documents) that can be authenticated, prevent unauthorized copying of their content and, in the case of printed …


Archetype Alignment: A Two-Level Driven Semantic Matching Approach To Interoperability In The Clinical Domain, Damon Berry, Jesus Bisbal Jan 2009

Archetype Alignment: A Two-Level Driven Semantic Matching Approach To Interoperability In The Clinical Domain, Damon Berry, Jesus Bisbal

Conference Papers

Semantic interoperability between electronic health record systems and other information systems in the health domain implies agreement about the structure and the meaning of the information that is communicated. There are still a number of similar but different EHR system approaches. Some of the newer approaches adopt the two-layer model approach where a generic reference model is constrained by archetypes into valid clinical concepts which can be exchanged. The meaning of the concepts that are represented by an archetype can be conveyed by embedding codes from a commonly recognised terminology at appropriate points in the archetype. However, as the number …


Patient-Centred Laboratory Validation Using Software Agents, John Mcgrory, Jane Grimson, Frank Clarke, Peter Gaffney Jan 2008

Patient-Centred Laboratory Validation Using Software Agents, John Mcgrory, Jane Grimson, Frank Clarke, Peter Gaffney

Conference Papers

Guidelines are self-contained documents which healthcare professionals reference to obtain knowledge about a specific condition or process. They interface with these documents and apply known facts about specific patients to gain useful supportive information to aid in developing a diagnosis or manage a condition. To automate this process a series of Standard Operating Procedures (SOP) and workflow processes are constructed using the contents of these documents in order to manage the validation flow of a patient sample. These processes decompose the guidelines into workflow plans, which are then called using condition triggers controlled by a centralised management engine. The software …


Design Of A Wireless System For Patient-Hospital Communication And Result Validation In Point Of Care Testing, John Mcgrory, Owen Lynch, Eugene Coyle Jan 2005

Design Of A Wireless System For Patient-Hospital Communication And Result Validation In Point Of Care Testing, John Mcgrory, Owen Lynch, Eugene Coyle

Conference Papers

This paper discuses mobile phone (cell phone) and wireless applications for linking patients who manage their healthcare outside the hospital using Point of Care Testing (POCT) to hospital information systems (HIS). Certain medical conditions require patients to manage their healthcare by performing on themselves POC testing and act faithfully on the result. This raises quality control issue, as these POC samples and testing procedures are not independently overseen by professional hospital staff. In hospitals, samples taken by clinicians are validated by hi-tech computerised validation systems to ensure plausibility, before physicians rely on them. Patients in the home must often use …