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learning analytics

Catherine Delves-Yates, Andrea Stockl, Jenny Moore
BACKGROUND: Concept analysis is frequently the first step novice nurse researchers take when beginning their work. However, the value of concept analysis in generating theory is debated, and although there are many models researchers can use, few provide guidance for applying them or overviews of their philosophical underpinnings. AIM: To share learning about challenges encountered when undertaking concept analysis and to present an adaptation of Rodgers ( 1989 ) model created to overcome these...
March 16, 2018: Nurse Researcher
Fernando Yepes-Calderon, Marvin D Nelson, J Gordon McComb
The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and access it at a voxel level, decrypted and uncompressed that allows analytical capabilities while not perturbing the system's daily operation. Additionally, the strategy is secure and vendor independent. Cerebral ventricular volume is important for the diagnosis and treatment of many neurological disorders...
2018: PloS One
Cedric Manlhiot
No abstract text is available yet for this article.
March 12, 2018: European Heart Journal Cardiovascular Imaging
Vineet M Arora
With the advent of electronic medical records (EMRs) fueling the rise of big data, the use of predictive analytics, machine learning, and artificial intelligence are touted as transformational tools to improve clinical care. While major investments are being made in using big data to transform health care delivery, little effort has been directed toward exploiting big data to improve graduate medical education (GME). Because our current system relies on faculty observations of competence, it is not unreasonable to ask whether big data in the form of clinical EMRs and other novel data sources can answer questions of importance in GME such as when is a resident ready for independent practice...
March 13, 2018: Academic Medicine: Journal of the Association of American Medical Colleges
Zarrar Shehzad, Gregory McCarthy
Whether category information is discretely localized or represented widely in the brain remains a contentious issue. Early functional MRI studies supported the localizationist perspective that category information was represented in discrete brain regions. More recent fMRI studies using machine learning pattern classification techniques provide evidence for widespread distributed representations. However, these latter studies have not typically accounted for shared information. Here, we find strong support for distributed representations when brain regions are considered separately...
March 14, 2018: Journal of Neurophysiology
Veronica Restelli, Annemarie Taylor, Douglas Cochrane, Michael A Noble
BACKGROUND: This article reports on the findings of 12,278 laboratory related safety events that were reported through the British Columbia Patient Safety & Learning System Incident Reporting System. METHODS: The reports were collected from 75 hospital-based laboratories over a 33-month period and represent approximately 4.9% of all incidents reported. RESULTS: Consistent with previous studies 76% of reported incidents occurred during the pre-analytic phase of the laboratory cycle, with twice as many associated with collection problems as with clerical problems...
June 27, 2017: Diagnosis
Dragana Milutinović, Robert Lovrić, Dragana Simin
BACKGROUND: There is an implicit expectation for medical sciences students to work together effectively as members of health-care team, and interprofessional education is therefore widely accepted. Students' attitudes, which are affected by various factors, have been recognized as the most important predictors of successful implementation of interprofessional education with the aim of developing collaborative practice. The Readiness for Interprofessional Learning Scale has often been used in studies to measure these perspectives...
March 8, 2018: Nurse Education Today
Paul T Cirino, Yusra Ahmed, Jeremy Miciak, W Pat Taylor, Elyssa H Gerst, Marcia A Barnes
OBJECTIVE: Executive function (EF) is a commonly used but difficult to operationalize construct. In this study, we considered EF and related components as they are commonly presented in the neuropsychological literature, as well as the literatures of developmental, educational, and cognitive psychology. These components have not previously been examined simultaneously, particularly with this level of comprehensiveness, and/or at this age range or with this sample size. We expected that the EF components would be separate but related, and that a bifactor model would best represent the data relative to alternative models...
February 2018: Neuropsychology
Erdem Varol, Aristeidis Sotiras, Christos Davatzikos
Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion...
March 7, 2018: NeuroImage
Reiner Salzer
No abstract text is available yet for this article.
March 9, 2018: Analytical and Bioanalytical Chemistry
Muhammed Veli, Aydogan Ozcan
We present a cost-effective and portable platform based on contact lenses for non-invasively detecting Staphylococcus aureus, which is part of the human ocular microbiome and resides on the cornea and conjunctiva. Using Staphylococcus aureus-specific antibodies and a surface chemistry protocol that is compatible with human tear, contact lenses are designed to specifically capture Staphylococcus aureus. After the bacteria capture on the lens, and right before its imaging, the captured bacteria are tagged with surface-functionalized polystyrene microparticles...
March 9, 2018: ACS Nano
Nagesh Shukla, Markus Hagenbuchner, Khin Than Win, Jack Yang
BACKGROUND: Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to assess/predict the survival prospects of patients. OBJECTIVE: The main objectives of this paper is to develop a robust data analytical model which can assist in (i) a better understanding of breast cancer survivability in presence of missing data, (ii) providing better insights into factors associated with patient survivability, and (iii) establishing cohorts of patients that share similar properties...
March 2018: Computer Methods and Programs in Biomedicine
Fei Jiang, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, Yongjun Wang
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data...
December 2017: Stroke and Vascular Neurology
John Grundy, Kon Mouzakis, Rajesh Vasa, Andrew Cain, Maheswaree Curumsing, Mohamed Abdelrazek, Niroshine Fernando
By the 2050, it is estimated that the proportion of people over the age of 80 will have risen from 3.9% to 9.1% of population of Organisation for Economic Cooperation and Development countries. A large proportion of these people will need significant help to manage various chronic illnesses, including dementia, heart disease, diabetes, limited physical movement and many others. Current approaches typically focus on acute episodes of illness and are not well designed to provide adequately for daily living care support...
2018: Studies in Health Technology and Informatics
Marcos Daou, Keith R Lohse, Matthew W Miller
Recent evidence suggests practicing a motor skill with the expectation of teaching it enhances learning by increasing information processing during motor preparation. However, the specific motor preparatory processes remain unknown. The present study sought to address this shortcoming by employing EEG to assess participants' motor preparatory processes while they completed a golf putting pretest, and then practiced putting with the expectation of (a) teaching another participant how to putt the next day (teach group, n = 30), or (b) being tested on their putting the next day (test group, n = 30)...
March 2, 2018: International Journal of Psychophysiology
Valeriya Naumova, Karin Schnass
This paper extends the recently proposed and theoretically justified iterative thresholding and K residual means (ITKrM) algorithm to learning dictionaries from incomplete/masked training data (ITKrMM). It further adapts the algorithm to the presence of a low-rank component in the data and provides a strategy for recovering this low-rank component again from incomplete data. Several synthetic experiments show the advantages of incorporating information about the corruption into the algorithm. Further experiments on image data confirm the importance of considering a low-rank component in the data and show that the algorithm compares favourably to its closest dictionary learning counterparts, wKSVD and BPFA, either in terms of computational complexity or in terms of consistency between the dictionaries learned from corrupted and uncorrupted data...
2018: EURASIP Journal on Advances in Signal Processing
Donald L Chi, Peter Milgrom, Jane Gillette
Purpose: The purpose of this study was to use qualitative methods to describe the key lessons learned during the stakeholder engagement stage of planning a randomized clinical trial comparing outcomes of silver diamine fluoride (SDF) as an alternative to pit-and-fissure sealants in a school-based delivery system. Methods: Eighteen caregivers and community-based stakeholders with involvement in the school-based sealant program Sealants for Smiles from the state of Montana, were recruited for this qualitative study...
February 2018: Journal of Dental Hygiene: JDH
Fernando Aparicio, María Luz Morales-Botello, Margarita Rubio, Asunción Hernando, Rafael Muñoz, Hugo López-Fernández, Daniel Glez-Peña, Florentino Fdez-Riverola, Manuel de la Villa, Manuel Maña, Diego Gachet, Manuel de Buenaga
BACKGROUND: Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emerging disciplines such as 'educational data mining' and 'learning analytics and knowledge' have provided clear examples of the importance of the use of artificial intelligence techniques in education. OBJECTIVE: The main objective of this study was to gather expert opinions regarding the benefits of using complementary methods that are supported by intelligent systems, specifically, by intelligent information access systems, when processing texts written in natural language and the benefits of using these methods as companion tools to the learning activities that are employed by biomedical and health sciences teachers...
April 2018: International Journal of Medical Informatics
Hope T Jackson, Monica T Young, H Alejandro Rodriguez, Andrew S Wright
BACKGROUND: Facebook is a popular online social networking platform increasingly used for professional collaboration. Literature regarding use of Facebook for surgeon professional development and education is limited. The Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) has established a Facebook group dedicated to discussion of surgery of the esophagus, stomach, and small intestine-the "SAGES Foregut Surgery Masters Program." The aim of this study is to examine how this forum is used for professional development, education, and quality improvement...
March 1, 2018: Surgical Endoscopy
(no author information available yet)
The field of systems immunology has grown extensively over the last few years, spurred by the generation of large datasets, new analytical tools, and modeling approaches. In this piece and its counterpart in Trends in Immunology [], eight authors discuss what immunologists can learn from systems biology and, conversely, how systems biologists can use immune cells as a model and outline the many directions this interdisciplinary field can expand in...
February 28, 2018: Cell Systems
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