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Problem based learning

Devis Peressutti, Matthew Sinclair, Wenjia Bai, Thomas Jackson, Jacobus Ruijsink, David Nordsletten, Liya Asner, Myrianthi Hadjicharalambous, Christopher A Rinaldi, Daniel Rueckert, Andrew P King
We present a framework for combining a cardiac motion atlas with non-motion data. The atlas represents cardiac cycle motion across a number of subjects in a common space based on rich motion descriptors capturing 3D displacement, velocity, strain and strain rate. The non-motion data are derived from a variety of sources such as imaging, electrocardiogram (ECG) and clinical reports. Once in the atlas space, we apply a novel supervised learning approach based on random projections and ensemble learning to learn the relationship between the atlas data and some desired clinical output...
October 11, 2016: Medical Image Analysis
Lisa J Meltzer
Research in the field of pediatric sleep has grown significantly in the past 25 years. However, because much remains to be learned about the complex and dynamic relationship between sleep and developmental psychopathology, this special issue of the Journal of Clinical Child and Adolescent Psychology was created to provide an influx of cutting-edge research on this important topic. This introduction provides an overview of the special issue, with articles focusing on what different measurement approaches tells us about the intersection of sleep and developmental psychopathology; the overlap between interventions for sleep and anxiety; sleep as a potential mechanism for the development of social, emotional, and behavioral problems; and how population-based studies can be used to consider the interaction between sleep, well-being, and symptoms of psychopathology...
October 21, 2016: Journal of Clinical Child and Adolescent Psychology
P Jauhar, P A Mossey, H Popat, J Seehra, P S Fleming
Background Undergraduate orthodontic teaching has been focused on developing an understanding of occlusal development in an effort to equip practitioners to make appropriate referrals for specialist-delivered care. However, there is a growing interest among general dentists in delivering more specialised treatments, including short-term orthodontic alignment. This study aimed to assess the levels of knowledge of occlusal problems among final year undergraduate dental students, as well as their interest in various orthodontics techniques and training...
October 21, 2016: British Dental Journal
Ryan Eshleman, Rahul Singh
BACKGROUND: Adverse drug events (ADEs) constitute one of the leading causes of post-therapeutic death and their identification constitutes an important challenge of modern precision medicine. Unfortunately, the onset and effects of ADEs are often underreported complicating timely intervention. At over 500 million posts per day, Twitter is a commonly used social media platform. The ubiquity of day-to-day personal information exchange on Twitter makes it a promising target for data mining for ADE identification and intervention...
October 6, 2016: BMC Bioinformatics
Edna Ruiz Magpantay-Monroe
The military and veteran populations in the U. S. state of Hawaii have a strong presence in the local communities. It was this substantial presence that provided the impetus to integrate military and veteran health into a Bachelor's of Science in Nursing (BSN) curriculum. This exploratory study investigated the relationship between the integration of military and veteran health into a psychiatric mental health BSN curriculum and nursing students' understanding of the many facets of military veterans' health...
October 6, 2016: Nurse Education Today
Kelly Russell, Michael G Hutchison, Erin Selci, Jeff Leiter, Daniel Chateau, Michael J Ellis
BACKGROUND: Many concussion symptoms, such as headaches, vision problems, or difficulty remembering or concentrating may deleteriously affect school functioning. Our objective was to determine if academic performance was lower in the academic calendar year that students sustain a concussion compared to the previous year when they did not sustain a concussion. METHODS: Using Manitoba Health and Manitoba Education data, we conducted a population-based, controlled before-after study from 2005-2006 to 2010-2011 academic years...
2016: PloS One
Jiangming Sun, Yang De Marinis, Peter Osmark, Pratibha Singh, Annika Bagge, Bérengère Valtat, Petter Vikman, Peter Spégel, Hindrik Mulder
RNA editing is a post-transcriptional alteration of RNA sequences that, via insertions, deletions or base substitutions, can affect protein structure as well as RNA and protein expression. Recently, it has been suggested that RNA editing may be more frequent than previously thought. A great impediment, however, to a deeper understanding of this process is the paramount sequencing effort that needs to be undertaken to identify RNA editing events. Here, we describe an in silico approach, based on machine learning, that ameliorates this problem...
2016: PloS One
Susan O Griffin, Liang Wei, Barbara F Gooch, Katherine Weno, Lorena Espinoza
BACKGROUND: Tooth decay is one of the greatest unmet treatment needs among children. Pain and suffering associated with untreated dental disease can lead to problems with eating, speaking, and learning. School-based dental sealant programs (SBSP) deliver a highly effective intervention to prevent tooth decay in children who might not receive regular dental care. SBSPs benefits exceed their costs when they target children at high risk for tooth decay. METHODS: CDC used data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014 to estimate current prevalences of sealant use and untreated tooth decay among low-income (≤185% of federal poverty level) and higher-income children aged 6-11 years and compared these estimates with 1999-2004 NHANES data...
October 21, 2016: MMWR. Morbidity and Mortality Weekly Report
Hasseeb Azzawi, Jingyu Hou, Yong Xiang, Russul Alanni
Lung cancer is a leading cause of cancer-related death worldwide. The early diagnosis of cancer has demonstrated to be greatly helpful for curing the disease effectively. Microarray technology provides a promising approach of exploiting gene profiles for cancer diagnosis. In this study, the authors propose a gene expression programming (GEP)-based model to predict lung cancer from microarray data. The authors use two gene selection methods to extract the significant lung cancer related genes, and accordingly propose different GEP-based prediction models...
October 2016: IET Systems Biology
Yun Lin, Chao Wang, Jiaxing Wang, Zheng Dou
Cognitive radio sensor networks are one of the kinds of application where cognitive techniques can be adopted and have many potential applications, challenges and future research trends. According to the research surveys, dynamic spectrum access is an important and necessary technology for future cognitive sensor networks. Traditional methods of dynamic spectrum access are based on spectrum holes and they have some drawbacks, such as low accessibility and high interruptibility, which negatively affect the transmission performance of the sensor networks...
October 12, 2016: Sensors
Richard J E James, Claire O'Malley, Richard J Tunney
This manuscript reviews the extant literature on key issues related to mobile gambling and considers whether the potential risks of harm emerging from this platform are driven by pre-existing comorbidities or by psychological processes unique to mobile gambling. We propose an account based on associative learning that suggests this form of gambling is likely to show distinctive features compared with other gambling technologies. Smartphones are a rapidly growing platform on which individuals can gamble using specifically designed applications, adapted websites or text messaging...
October 18, 2016: British Journal of Psychology
Akshansh Gupta, Dhirendra Kumar
A brain computer interface (BCI) is a communication system by which a person can send messages or requests for basic necessities without using peripheral nerves and muscles. Response to mental task-based BCI is one of the privileged areas of investigation. Electroencephalography (EEG) signals are used to represent the brain activities in the BCI domain. For any mental task classification model, the performance of the learning model depends on the extraction of features from EEG signal. In literature, wavelet transform and empirical mode decomposition are two popular feature extraction methods used to analyze a signal having non-linear and non-stationary property...
September 3, 2016: Brain Informatics
Xinpei Ma, Chun-An Chou, Hiroki Sayama, Wanpracha Art Chaovalitwongse
Many neuroscience studies have been devoted to understand brain neural responses correlating to cognition using functional magnetic resonance imaging (fMRI). In contrast to univariate analysis to identify response patterns, it is shown that multi-voxel pattern analysis (MVPA) of fMRI data becomes a relatively effective approach using machine learning techniques in the recent literature. MVPA can be considered as a multi-objective pattern classification problem with the aim to optimize response patterns, in which informative voxels interacting with each other are selected, achieving high classification accuracy associated with cognitive stimulus conditions...
September 2016: Brain Informatics
Byron C Wallace, Joël Kuiper, Aakash Sharma, Mingxi Brian Zhu, Iain J Marshall
Systematic reviews underpin Evidence Based Medicine (EBM) by addressing precise clinical questions via comprehensive synthesis of all relevant published evidence. Authors of systematic reviews typically define a Population/Problem, Intervention, Comparator, and Outcome (a PICO criteria) of interest, and then retrieve, appraise and synthesize results from all reports of clinical trials that meet these criteria. Identifying PICO elements in the full-texts of trial reports is thus a critical yet time-consuming step in the systematic review process...
2016: Journal of Machine Learning Research: JMLR
G Iakimova, S Dimitrova, T Burté
OBJECTIVES: Computer-delivered Cognitive Behavioral Therapies (C-CBT) are emerging as therapeutic techniques which contribute to overcome the barriers of health care access in adult populations with depression. The C-CBTs provide CBT techniques in a highly structured format comprising a number of educational lessons, homework, multimedia illustrations and supplementary materials via interactive computer interfaces. Programs are often administrated with a minimal or regular support provided by a clinician or a technician via email, telephone, online forums, or during face-to-face consultations...
October 10, 2016: L'Encéphale
Anthony J Rosellini, John Monahan, Amy E Street, Eric D Hill, Maria Petukhova, Ben Y Reis, Nancy A Sampson, David M Benedek, Paul Bliese, Murray B Stein, Robert J Ursano, Ronald C Kessler
Growing concerns exist about violent crimes perpetrated by U.S. military personnel. Although interventions exist to reduce violent crimes in high-risk populations, optimal implementation requires evidence-based targeting. The goal of the current study was to use machine learning methods (stepwise and penalized regression; random forests) to develop models to predict minor violent crime perpetration among U.S. Army soldiers. Predictors were abstracted from administrative data available for all 975,057 soldiers in the U...
September 30, 2016: Journal of Psychiatric Research
Yan Li, Ruiping Wang, Zhen Cui, Shiguang Shan, Xilin Chen
We address the problem of face video retrieval in TV-series which searches video clips based on the presence of specific character, given one face track of his/her. This is tremendously challenging because on one hand, faces in TV-series are captured in largely uncontrolled conditions with complex appearance variations, and on the other hand retrieval task typically needs efficient representation with low time and space complexity. To handle this problem, we propose a compact and discriminative representation for the huge body of video data, named Compact Video Code (CVC)...
October 10, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
N Ramaiah, Ajay Kumar
Iris recognition systems are increasingly deployed for large-scale applications such as national ID programs which continue to acquire millions of iris images to establish identity among billions. However with the availability of variety of iris sensors that are deployed for the iris imaging under different illumination/environment, significant performance degradation is expected while matching such iris images acquired under two different domains (either sensor-specific or wavelength-specific). This paper develops a domain adaptation framework to address this problem and introduces a new algorithm using Markov random fields (MRF) model to significantly improve cross-domain iris recognition...
October 10, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Valerie B Shapiro, B K Elizabeth Kim, Jennifer L Robitaille, Paul A LeBuffe
The Devereux Student Strengths Assessment Mini (DESSA-Mini; Naglieri, LeBuffe, & Shapiro, 2011/2014) was designed to overcome practical obstacles to universal prevention screening. This article seeks to determine whether an entirely strength-based, 8-item screening instrument achieves technical accuracy in routine practice. Data come from a district-wide implementation of a new social emotional learning (SEL) initiative designed to promote students' social-emotional competence. All students, kindergarten through Grade 8, were screened using the DESSA-Mini...
October 13, 2016: School Psychology Quarterly
Georgia Spiridon Karanasiou, Evanthia Eleftherios Tripoliti, Theofilos Grigorios Papadopoulos, Fanis Georgios Kalatzis, Yorgos Goletsis, Katerina Kyriakos Naka, Aris Bechlioulis, Abdelhamid Errachid, Dimitrios Ioannis Fotiadis
Heart failure (HF) is a chronic disease characterised by poor quality of life, recurrent hospitalisation and high mortality. Adherence of patient to treatment suggested by the experts has been proven a significant deterrent of the above-mentioned serious consequences. However, the non-adherence rates are significantly high; a fact that highlights the importance of predicting the adherence of the patient and enabling experts to adjust accordingly patient monitoring and management. The aim of this work is to predict the adherence of patients with HF, through the application of machine learning techniques...
September 2016: Healthcare Technology Letters
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