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https://www.readbyqxmd.com/read/28527481/rethinking-anatomy-how-to-overcome-challenges-of-medical-education-s-evolution
#1
REVIEW
Bruno Guimarães, Luís Dourado, Stanislav Tsisar, José Miguel Diniz, Maria Dulce Madeira, Maria Amélia Ferreira
INTRODUCTION: Due to scientific and technological development, Medical Education has been readjusting its focus and strategies. Medical curriculum has been adopting a vertical integration model, in which basic and clinical sciences coexist during medical instruction. This context favours the introduction of new complementary technology-based pedagogical approaches. Thus, even traditional core sciences of medical curriculum, like Anatomy, are refocusing their teaching/learning paradigm...
February 27, 2017: Acta Médica Portuguesa
https://www.readbyqxmd.com/read/28516901/eeg-source-space-analysis-of-the-supervised-factor-analytic-approach-for-the-classification-of-multi-directional-arm-movement
#2
Vikram Shenoy Handiru, A P Vinod, Cuntai Guan
OBJECTIVE: In electroencephalography (EEG)-based brain-computer interface (BCI) systems for motor control tasks the conventional practice is to decode motor intentions by using scalp EEG. However, scalp EEG only reveals certain limited information about the complex tasks of movement with a higher degree of freedom. Therefore, our objective is to investigate the effectiveness of source-space EEG in extracting relevant features that discriminate arm movement in multiple directions. APPROACH: We have proposed a novel feature extraction algorithm based on supervised factor analysis that models the data from source-space EEG...
May 18, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28515060/barriers-and-facilitators-experienced-in-collaborative-prospective-research-in-orthopaedic-oncology-a-qualitative-study
#3
J S Rendon, M Swinton, N Bernthal, M Boffano, T Damron, N Evaniew, P Ferguson, M Galli Serra, W Hettwer, P McKay, B Miller, L Nystrom, W Parizzia, P Schneider, A Spiguel, R Vélez, K Weiss, J P Zumárraga, M Ghert
OBJECTIVES: As tumours of bone and soft tissue are rare, multicentre prospective collaboration is essential for meaningful research and evidence-based advances in patient care. The aim of this study was to identify barriers and facilitators encountered in large-scale collaborative research by orthopaedic oncological surgeons involved or interested in prospective multicentre collaboration. METHODS: All surgeons who were involved, or had expressed an interest, in the ongoing Prophylactic Antibiotic Regimens in Tumour Surgery (PARITY) trial were invited to participate in a focus group to discuss their experiences with collaborative research in this area...
May 2017: Bone & Joint Research
https://www.readbyqxmd.com/read/28509940/medico-legal-assessment-of-methamphetamine-and-amphetamine-serum-concentrations-what-can-we-learn-from-survived-intoxications
#4
Marco Weber, Rüdiger Lessig, Carolin Richter, Axel P Ritter, Ilona Weiß
Medico-legal experts are increasingly enlisted to assess the methamphetamine and amphetamine serum concentrations after a criminal offense. However, since criminal users rarely provide useful information to medico-legal experts regarding the substances abused, when the substance(s) was/were used, dose of ingestion tools are needed to interpret the analytical data, which can be used as objective evidence in such cases. A comparative series of methamphetamine and amphetamine serum concentrations were used to analyze the frequency of concentrations, to determine methamphetamine/amphetamine concentration ratios, and prove them as a tool to distinguish pure methamphetamine from mixed amphetamine/methamphetamine ingestion...
May 16, 2017: International Journal of Legal Medicine
https://www.readbyqxmd.com/read/28508802/knowledge-engineering-as-a-component-of-the-curriculum-for-medical-cybernetists
#5
Sergey Karas, Arthur Konev
According to a new state educational standard, students who have chosen medical cybernetics as their major must develop a knowledge engineering competency. Previously, in the course "Clinical cybernetics" while practicing project-based learning students were designing automated workstations for medical personnel using client-server technology. The purpose of the article is to give insight into the project of a new educational module "Knowledge engineering". Students will acquire expert knowledge by holding interviews and conducting surveys, and then they will formalize it...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28508785/assessing-the-educational-needs-of-health-information-management-staff-of-the-mashhad-university-of-medical-sciences-iran
#6
Khalil Kimiafar, Abbas Sheikhtaheri, Masoumeh Sarbaz, Masoumeh Hoseini
Health information management (HIM) professionals have a combination of skills and, at the same time, the demand for their skills in the health system is increasing rapidly. This study aimed to assess the educational needs of the HIM staff in Iran. This descriptive analytical study was conducted in eight teaching hospitals. It was found that the maximum educational needs concerned the knowledge of medical terminology, occupational safety, legal aspects, the newest rules and regulations, and ministry guidelines, while the least of the felt needs related to insurance and other aspects of registry, data ownership, and data quality...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28508373/an-advanced-omic-approach-to-identify-co-regulated-clusters-and-transcription-regulation-network-with-agct-and-shoe-methods
#7
Natalia Polouliakh, Richard Nock
To obtain the global picture of genetic machinery for massive high-throughput gene expression data, novel data-driven unsupervised learning approaches are becoming essentially important. For this purpose, basic analytic workflow has been established and should include two steps: first, unsupervised clustering to identify genes with similar behavior upon exposure to a signal, and second, identification of transcription factors regulating those genes. In this chapter, we will describe an advanced tool that can be used for analyzing and characterizing large-scale time-series gene expression composed of a two-step approach...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28508126/what-s-the-point-golden-and-labrador-retrievers-living-in-kennels-do-not-understand-human-pointing-gestures
#8
Biagio D'Aniello, Alessandra Alterisio, Anna Scandurra, Emanuele Petremolo, Maria Rosaria Iommelli, Massimo Aria
In many studies that have investigated whether dogs' capacities to understand human pointing gestures are aspects of evolutionary or developmental social competences, family-owned dogs have been compared to shelter dogs. However, for most of these studies, the origins of shelter dogs were unknown. Some shelter dogs may have lived with families before entering shelters, and from these past experiences, they may have learned to understand human gestures. Furthermore, there is substantial variation in the methodology and analytic approaches used in such studies (e...
May 15, 2017: Animal Cognition
https://www.readbyqxmd.com/read/28504948/substructural-regularization-with-data-sensitive-granularity-for-sequence-transfer-learning
#9
Shichang Sun, Hongbo Liu, Jiana Meng, C L Philip Chen, Yu Yang
Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy...
May 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28503157/a-review-of-self-regulated-learning-six-models-and-four-directions-for-research
#10
REVIEW
Ernesto Panadero
Self-regulated learning (SRL) includes the cognitive, metacognitive, behavioral, motivational, and emotional/affective aspects of learning. It is, therefore, an extraordinary umbrella under which a considerable number of variables that influence learning (e.g., self-efficacy, volition, cognitive strategies) are studied within a comprehensive and holistic approach. For that reason, SRL has become one of the most important areas of research within educational psychology. In this paper, six models of SRL are analyzed and compared; that is, Zimmerman; Boekaerts; Winne and Hadwin; Pintrich; Efklides; and Hadwin, Järvelä and Miller...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28495010/predictive-analytics-through-machine-learning-in-the-clinical-settings
#11
EDITORIAL
Shabbir Syed-Abdul, Usman Iqbal, Yu-Chuan Jack Li
No abstract text is available yet for this article.
June 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28494123/ecological-momentary-interventions-for-depression-and-anxiety
#12
Stephen M Schueller, Adrian Aguilera, David C Mohr
Ecological momentary interventions (EMIs) are becoming more popular and more powerful resources for the treatment and prevention of depression and anxiety due to advances in technological capacity and analytic sophistication. Previous work has demonstrated that EMIs can be effective at reducing symptoms of depression and anxiety as well as related outcomes of stress and at increasing positive psychological functioning. In this review, we highlight the differences between EMIs and other forms of treatment due to the nature of EMIs to be deeply integrated into the fabric of people's day-to-day lives...
May 11, 2017: Depression and Anxiety
https://www.readbyqxmd.com/read/28491241/fifteen-years-of-bone-marrow-mononuclear-cell-therapy-in-acute-myocardial-infarction
#13
REVIEW
Miruna Mihaela Micheu, Maria Dorobantu
In spite of modern treatment, acute myocardial infarction (AMI) still carries significant morbidity and mortality worldwide. Even though standard of care therapy improves symptoms and also long-term prognosis of patients with AMI, it does not solve the critical issue, specifically the permanent damage of cardiomyocytes. As a result, a complex process occurs, namely cardiac remodeling, which leads to alterations in cardiac size, shape and function. This is what has driven the quest for unconventional therapeutic strategies aiming to regenerate the injured cardiac and vascular tissue...
April 26, 2017: World Journal of Stem Cells
https://www.readbyqxmd.com/read/28488257/a-comparison-of-four-software-programs-for-implementing-decision-analytic-cost-effectiveness-models
#14
REVIEW
Chase Hollman, Mike Paulden, Petros Pechlivanoglou, Christopher McCabe
The volume and technical complexity of both academic and commercial research using decision analytic modelling has increased rapidly over the last two decades. The range of software programs used for their implementation has also increased, but it remains true that a small number of programs account for the vast majority of cost-effectiveness modelling work. We report a comparison of four software programs: TreeAge Pro, Microsoft Excel, R and MATLAB. Our focus is on software commonly used for building Markov models and decision trees to conduct cohort simulations, given their predominance in the published literature around cost-effectiveness modelling...
May 9, 2017: PharmacoEconomics
https://www.readbyqxmd.com/read/28484384/mechanisms-of-winner-take-all-and-group-selection-in-neuronal-spiking-networks
#15
Yanqing Chen
A major function of central nervous systems is to discriminate different categories or types of sensory input. Neuronal networks accomplish such tasks by learning different sensory maps at several stages of neural hierarchy, such that different neurons fire selectively to reflect different internal or external patterns and states. The exact mechanisms of such map formation processes in the brain are not completely understood. Here we study the mechanism by which a simple recurrent/reentrant neuronal network accomplish group selection and discrimination to different inputs in order to generate sensory maps...
2017: Frontiers in Computational Neuroscience
https://www.readbyqxmd.com/read/28480714/nanoparticle-protein-interactions-therapeutic-approaches-and-supramolecular-chemistry
#16
Mathis Kopp, Sebastian Kollenda, Matthias Epple
Research on nanoparticles has evolved into a major topic in chemistry. Concerning biomedical research, nanoparticles have decisively entered the field, creating the area of nanomedicine where nanoparticles are used for drug delivery, imaging, and tumor targeting. Besides these functions, scientists have addressed the specific ways in which nanoparticles interact with biomolecules, with proteins being the most prominent example. Depending on their size, shape, charge, and surface functionality, specifically designed nanoparticles can interact with proteins in a defined way...
May 8, 2017: Accounts of Chemical Research
https://www.readbyqxmd.com/read/28479353/some-lessons-learned-from-a-comparison-between-sedimentation-velocity-analytical-ultracentrifugation-and-size-exclusion-chromatography-to-characterize-and-quantify-protein-aggregates
#17
Aditya V Gandhi, Mark R Pothecary, David L Bain, John F Carpenter
There are numerous problems with size exclusion chromatography (SEC), which often lead to inaccuracies in protein aggregate characterization. Hence, this study tested sedimentation velocity analytical ultracentrifugation (SV-AUC) as an orthogonal tool to SEC for quantifying the monomer and aggregates in intravenous immunoglobulin (IVIg) formulations. IVIg samples were subjected to agitation stress and analyzed using SEC mobile phases composed of 200 mM sodium phosphate (pH 7.0) with 0, 50, 100, 200 or 400 mM of NaCl...
May 4, 2017: Journal of Pharmaceutical Sciences
https://www.readbyqxmd.com/read/28464332/a-comparison-of-risk-prediction-methods-using-repeated-observations-an-application-to-electronic-health-records-for-hemodialysis
#18
Benjamin A Goldstein, Gina Maria Pomann, Wolfgang C Winkelmayer, Michael J Pencina
An increasingly important data source for the development of clinical risk prediction models is electronic health records (EHRs). One of their key advantages is that they contain data on many individuals collected over time. This allows one to incorporate more clinical information into a risk model. However, traditional methods for developing risk models are not well suited to these irregularly collected clinical covariates. In this paper, we compare a range of approaches for using longitudinal predictors in a clinical risk model...
May 2, 2017: Statistics in Medicine
https://www.readbyqxmd.com/read/28457678/research-pearls-the-significance-of-statistics-and-perils-of-pooling-part-2-predictive-modeling
#19
Erik Hohmann, Merrick J Wetzler, Ralph B D'Agostino
The focus of predictive modeling or predictive analytics is to use statistical techniques to predict outcomes and/or the results of an intervention or observation for patients that are conditional on a specific set of measurements taken on the patients prior to the outcomes occurring. Statistical methods to estimate these models include using such techniques as Bayesian methods; data mining methods, such as machine learning; and classical statistical models of regression such as logistic (for binary outcomes), linear (for continuous outcomes), and survival (Cox proportional hazards) for time-to-event outcomes...
April 27, 2017: Arthroscopy: the Journal of Arthroscopic & related Surgery
https://www.readbyqxmd.com/read/28449114/neuro-symbolic-representation-learning-on-biological-knowledge-graphs
#20
Mona Alshahrani, Mohammed Asif Khan, Omar Maddouri, Akira R Kinjo, Núria Queralt-Rosinach, Robert Hoehndorf
Motivation: Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs...
April 25, 2017: Bioinformatics
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