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https://www.readbyqxmd.com/read/28239917/decrease-in-mortality-of-adult-epilepsy-patients-since-1980-lessons-learned-from-a-hospital-based-cohort
#1
C A Granbichler, W Oberaigner, G Kuchukhidze, J-P Ndayisaba, A Ndayisaba, A Taylor, G Bauer, G Luef, E Trinka
BACKGROUND AND PURPOSE: Data on mortality in patients with epilepsy have been available since the 1800s. They consistently show a 2-3-fold increase compared to the general population. Despite major advances in diagnostic tools and treatment options, there is no evidence for a decrease in premature deaths. The temporal trend of mortality in a hospital-based epilepsy cohort over three decades was assessed. METHODS: A hospital-based incidence cohort was recruited from a specialized epilepsy outpatient clinic at Innsbruck Medical University between 1980 and 2007, divided by decade into three cohorts and followed for 5 years after initial epilepsy diagnosis...
February 27, 2017: European Journal of Neurology: the Official Journal of the European Federation of Neurological Societies
https://www.readbyqxmd.com/read/28239597/perceived-cognitive-deficits-are-associated-with-diabetes-self-management-in-a-multiethnic-sample
#2
Heather Cuevas, Alexa Stuifbergen
BACKGROUND: People with diabetes have almost twice the risk of developing cognitive impairment or dementia as do those without diabetes, and about half of older adults with diabetes will become functionally disabled or cognitively impaired. But diabetes requires complex self-management: patients must learn about the implications of their disease; manage their diets, physical activity, and medication; and monitor their blood glucose. Difficulties with cognition can hinder these activities...
2017: Journal of Diabetes and Metabolic Disorders
https://www.readbyqxmd.com/read/28239363/formal-and-informal-learning-and-first-year-psychology-students-development-of-scientific-thinking-a-two-wave-panel-study
#3
Demet Soyyılmaz, Laura M Griffin, Miguel H Martín, Šimon Kucharský, Ekaterina D Peycheva, Nina Vaupotič, Peter A Edelsbrunner
Scientific thinking is a predicate for scientific inquiry, and thus important to develop early in psychology students as potential future researchers. The present research is aimed at fathoming the contributions of formal and informal learning experiences to psychology students' development of scientific thinking during their 1st-year of study. We hypothesize that informal experiences are relevant beyond formal experiences. First-year psychology student cohorts from various European countries will be assessed at the beginning and again at the end of the second semester...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28237930/video-based-pedestrian-re-identification-by-adaptive-spatio-temporal-appearance-model
#4
Wei Zhang, Bingpeng Ma, Kan Liu, Rui Huang
Pedestrian re-identification is a difficult problem due to the large variations in a person's appearance caused by different poses and viewpoints, illumination changes, and occlusions. Spatial alignment is commonly used to address these issues by treating the appearance of different body parts independently. However, a body part can also appear differently during different phases of an action. In this paper we consider the temporal alignment problem, in addition to the spatial one, and propose a new approach that takes the video of a walking person as input and builds a spatio-temporal appearance representation for pedestrian re-identification...
February 20, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28237850/light-at-the-end-of-the-tunnel-new-graduate-nurses-accounts-of-resilience-a-qualitative-study-using-photovoice
#5
Siti Namira Binte Abdul Wahab, Siti Zubaidah Mordiffi, Emily Ang, Violeta Lopez
BACKGROUND: Resilience is the ability to overcome any stressful situation. The ability to bounce back is said to enable a person to emerge stronger, perform better, and become more confident and selfefficient. The new graduate nurses' journey is a stressful experience as they become immersed in the day-to-day work pressures. OBJECTIVE: The study explored the new graduate nurses' accounts of resilience and the facilitating and impeding factors in building their resilience...
February 14, 2017: Nurse Education Today
https://www.readbyqxmd.com/read/28237826/treatment-considerations-for-depression-research-in-older-married-couples-a-dyadic-case-study
#6
Sarah T Stahl, Juleen Rodakowski, Ariel G Gildengers, Charles F Reynolds, Jennifer Q Morse, Kevin Rico, Meryl A Butters
OBJECTIVE: Critical gaps remain in understanding optimal approaches to intervening with older couples. The focus of this report is to describe the pros and cons of incorporating spousal dyads into depression-prevention research. METHODS: In an intervention development study, the authors administered problem-solving therapy (PST) dyadically to participants with mild cognitive impairment (MCI) and their caregivers. Dyads worked with the same interventionist in the same therapy session...
January 4, 2017: American Journal of Geriatric Psychiatry
https://www.readbyqxmd.com/read/28237585/invited-review-determinants-of-farmers-adoption-of-management-based-strategies-for-infectious-disease-prevention-and-control
#7
Caroline Ritter, Jolanda Jansen, Steven Roche, David F Kelton, Cindy L Adams, Karin Orsel, Ron J Erskine, Geart Benedictus, Theo J G M Lam, Herman W Barkema
The prevention and control of endemic pathogens within and between farms often depends on the adoption of best management practices. However, farmers regularly do not adopt recommended measures or do not enroll in voluntary disease control programs. This indicates that a more comprehensive understanding of the influences and extension tools that affect farmers' management decisions is necessary. Based on a review of relevant published literature, we developed recommendations to support policy-makers, industry representatives, researchers, veterinarians, and other stakeholders when motivating farmers to adopt best management practices, and to facilitate the development and implementation of voluntary prevention and control programs for livestock diseases...
February 22, 2017: Journal of Dairy Science
https://www.readbyqxmd.com/read/28230751/the-feasibility-of-embedding-data-collection-into-the-routine-service-delivery-of-a-multi-component-program-for-high-risk-young-people
#8
Alice Knight, Alys Havard, Anthony Shakeshaft, Myfanwy Maple, Mieke Snijder, Bernie Shakeshaft
BACKGROUND: There is little evidence about how to improve outcomes for high-risk young people, of whom Indigenous young people are disproportionately represented, due to few evaluation studies of interventions. One way to increase the evidence is to have researchers and service providers collaborate to embed evaluation into the routine delivery of services, so program delivery and evaluation occur simultaneously. This study aims to demonstrate the feasibility of integrating best-evidence measures into the routine data collection processes of a service for high-risk young people, and identify the number and nature of risk factors experienced by participants...
February 20, 2017: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/28228573/grace-under-pressure-a-drama-based-approach-to-tackling-mistreatment-of-medical-students
#9
Karen M Scott, Špela Berlec, Louise Nash, Claire Hooker, Paul Dwyer, Paul Macneill, Jo River, Kimberley Ivory
A positive and respectful learning environment is fundamental to the development of professional identities in healthcare. Yet medical students report poor behaviour from healthcare professionals that contradict professionalism teaching. An interdisciplinary group designed and implemented a drama-based workshop series, based on applied theatre techniques, to help students develop positive professional qualities and interpersonal skills to deal with challenges in the healthcare setting. We piloted the workshops at the University of Sydney in 2015...
March 2017: Medical Humanities
https://www.readbyqxmd.com/read/28227913/online-learning-of-gait-models-for-calculation-of-gait-parameters
#10
Jamie L S Waugh, Anton Trinh, Ryan R Mohammed, William E McIlroy, Dana Kulic, Jamie L S Waugh, Anton Trinh, Ryan R Mohammed, William E McIlroy, Dana Kulic, Jamie L S Waugh, Dana Kulic, Anton Trinh, William E McIlroy, Ryan R Mohammed
This paper proposes a novel approach for gait analysis from wearable sensing, based on an adaptive periodic model of any gait signal. The proposed method learns a model of the gait cycle during online measurement, using a continuous representation that can adapt to inter and intra-personal variability by creating an individualized model. Once the algorithm has converged to the input signal, key gait events can be identified relative to the estimated gait phase; these events can then be used to calculate gait parameters...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227840/virtual-reality-for-pediatric-neuro-rehabilitation-adaptive-visual-feedback-of-movement-to-engage-the-mirror-neuron-system
#11
Roopeswar Kommalapati, Konstantinos P Michmizos, Roopeswar Kommalapati, Konstantinos P Michmizos, Roopeswar Kommalapati, Konstantinos P Michmizos
Sensorimotor therapy gives optimal results when patients are cognitively engaged into highly repetitive tasks, a goal that most children find hard to pursue. This paper presents the key developments of our ongoing effort to design an interactive rehabilitation environment that motivates physically impaired children throughout their therapy. The continuous motivation is achieved by the system adapting fundamental therapeutic components to the performance of each child. The relevant movement is mirrored to an animated character projected in front of the child...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227720/can-we-make-a-carpet-smart-enough-to-detect-falls
#12
Fadi Muheidat, Harry W Tyrer, Fadi Muheidat, Harry W Tyrer, Harry W Tyrer, Fadi Muheidat
In this paper, we have enhanced smart carpet, which is a floor based personnel detector system, to detect falls using a faster but low cost processor. Our hardware front end reads 128 sensors, with sensors output a voltage due to a person walking or falling on the carpet. The processor is Jetson TK1, which provides more computing power than before. We generated a dataset with volunteers who walked and fell to test our algorithms. Data obtained allowed examining data frames (a frame is a single scan of the carpet sensors) read from the data acquisition system...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227679/wildcard-a-wearable-virtual-reality-storytelling-tool-for-children-with-intellectual-developmental-disability
#13
Mirko Gelsomini, Franca Garzotto, Daniele Montesano, Daniele Occhiuto, Mirko Gelsomini, Franca Garzotto, Daniele Montesano, Daniele Occhiuto, Daniele Montesano, Franca Garzotto, Mirko Gelsomini, Daniele Occhiuto
Our research aims at supporting existing therapies for children with intellectual and developmental disorders (IDD). The personal and social autonomy is the desired end state to be achieved to enable a smooth integration in the real world. We developed and tested a framework for storytelling and learning activities that exploits an immersive virtual reality viewer to interact with target users. We co-designed our system with experts from the medical sector, identifying features that allow patients to stay focused on exercises to perform...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227651/adaptive-control-of-powered-transfemoral-prostheses-based-on-adaptive-dynamic-programming
#14
Yue Wen, Ming Liu, Jennie Si, He Helen Huang, Yue Wen, Ming Liu, Jennie Si, He Huang, He Helen Huang, Yue Wen, Ming Liu, Jennie Si
In this study, we developed and tested a novel adaptive controller for powered transfemoral prostheses. Adaptive dynamic programming (ADP) was implemented within the prosthesis control to complement the existing finite state impedance control (FS-IC) in a prototypic active-transfemoral prosthesis (ATP). The ADP controller interacts with the human user-prosthesis system, observes the prosthesis user's dynamic states during walking, and learns to personalize user performance properties via online adaptation to meet the individual user's objectives...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227226/learning-approaches-to-improve-prediction-of-drug-sensitivity-in-breast-cancer-patients
#15
Turki Turki, Zhi Wei, Turki Turki, Zhi Wei, Turki Turki, Zhi Wei
Predicting drug response to cancer disease is an important problem in modern clinical oncology that attracted increasing recent attention from various domains such as computational biology, machine learning, and data mining. Cancer patients respond differently to each cancer therapy owing to disease diversity, genetic factors, and environmental causes. Thus, oncologists aim to identify the effective therapies for cancer patients and avoid adverse drug reactions in patients. By predicting the drug response to cancer, oncologists gain full understanding of the effective treatments on each patient, which leads to better personalized treatment...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227214/activity-recognition-in-patients-with-lower-limb-impairments-do-we-need-training-data-from-each-patient
#16
Luca Lonini, Aakash Gupta, Konrad Kording, Arun Jayaraman, Luca Lonini, Aakash Gupta, Konrad Kording, Arun Jayaraman, Luca Lonini, Konrad Kording, Arun Jayaraman, Aakash Gupta
Machine learning allows detecting specific physical activities using data from wearable sensors. Such a quantification of patient mobility over time promises to accurately inform clinical decisions for physical rehabilitation. There are two strategies of setting up the machine learning problem: detect one patient's activities using data from the same patient (personal model) or detect their activities using data from other patients (global model), and we currently do not know if personal models are necessary...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227032/a-statistical-model-for-stroke-outcome-prediction-and-treatment-planning
#17
Abhishek Sengupta, Vaibhav Rajan, Sakyajit Bhattacharya, G R K Sarma, Abhishek Sengupta, Vaibhav Rajan, Sakyajit Bhattacharya, G R K Sarma, Abhishek Sengupta, Grk Sarma, Vaibhav Rajan, Sakyajit Bhattacharya
Stroke is a major cause of mortality and long-term disability in the world. Predictive outcome models in stroke are valuable for personalized treatment, rehabilitation planning and in controlled clinical trials. We design a new multi-class classification model to predict outcome in the short-term, the putative therapeutic window for several treatments. Our model addresses the challenges of class imbalance, where the training data is dominated by samples of a single class, and highly correlated predictor and outcome variables, which makes learning the effects of treatments on the outcome difficult...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227016/towards-sophisticated-learning-from-ehrs-increasing-prediction-specificity-and-accuracy-using-clinically-meaningful-risk-criteria
#18
Ieva Vasiljeva, Ognjen Arandjelovic, Ieva Vasiljeva, Ognjen Arandjelovic, Ieva Vasiljeva, Ognjen Arandjelovic
Computer based analysis of Electronic Health Records (EHRs) has the potential to provide major novel insights of benefit both to specific individuals in the context of personalized medicine, as well as on the level of population-wide health care and policy. The present paper introduces a novel algorithm that uses machine learning for the discovery of longitudinal patterns in the diagnoses of diseases. Two key technical novelties are introduced: one in the form of a novel learning paradigm which enables greater learning specificity, and another in the form of a risk driven identification of confounding diagnoses...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226945/transferring-knowledge-during-dyadic-interaction-the-role-of-the-expert-in-the-learning-process
#19
Edwin Johnatan Avila Mireles, Dalia De Santis, Pietro Morasso, Jacopo Zenzeri, Edwin Johnatan Avila Mireles, Dalia De Santis, Pietro Morasso, Jacopo Zenzeri, Jacopo Zenzeri, Pietro Morasso, Edwin Johnatan Avila Mireles, Dalia De Santis
Physical interaction between man and machines is increasing the interest of the research as well as the industrial community. It is known that physical coupling between active persons can be beneficial and increase the performance of the dyad compared to an individual. However, the factors that may result in performance benefits are still poorly understood. The aim of this work is to investigate how the different initial skill levels of the interacting partners influence the learning of a stabilization task...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226608/heart-beat-characterization-from-ballistocardiogram-signals-using-extended-functions-of-multiple-instances
#20
Changzhe Jiao, Princess Lyons, Alina Zare, Licet Rosales, Marjorie Skubic, Changzhe Jiao, Princess Lyons, Alina Zare, Licet Rosales, Marjorie Skubic, Princess Lyons, Alina Zare, Changzhe Jiao, Marjorie Skubic, Licet Rosales
A multiple instance learning (MIL) method, extended Function of Multiple Instances (eFUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The goal of this approach is to learn a personalized heartbeat "concept" for an individual. This heartbeat concept is a prototype (or "signature") that characterizes the heartbeat pattern for an individual in ballistocardiogram data. The eFUMI method models the problem of learning a heartbeat concept from a BCG signal as a MIL problem...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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