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https://www.readbyqxmd.com/read/28944324/surgeons-approach-toward-clinical-nutrition-a-survey-based-study
#1
Bahadır Osman Bozkırlı, Rıza Haldun Gündoğdu, Soner Akbaba, Turgay Sayın, Pamir Eren Ersoy
OBJECTIVE: Although many surgical patients face postoperative problems due to a poor nutritional status, there is evidence that many cases of malnutrition still go unnoticed and untreated in surgical wards. This study aims to define the current attitudes of surgeons toward nutritional screening and support. MATERIAL AND METHODS: A questionnaire with 13 questions was e-mailed to 1500 surgeons. Cross-queries were made over the responses. RESULTS: The response rate was 20...
2017: Turk J Surg
https://www.readbyqxmd.com/read/28943847/modeling-search-behaviors-during-the-acquisition-of-expertise-in-a-sequential-decision-making-task
#2
Cristóbal Moënne-Loccoz, Rodrigo C Vergara, Vladimir López, Domingo Mery, Diego Cosmelli
Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve...
2017: Frontiers in Computational Neuroscience
https://www.readbyqxmd.com/read/28943846/a-computational-model-for-the-automatic-diagnosis-of-attention-deficit-hyperactivity-disorder-based-on-functional-brain-volume
#3
Lirong Tan, Xinyu Guo, Sheng Ren, Jeff N Epstein, Long J Lu
In this paper, we investigated the problem of computer-aided diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) using machine learning techniques. With the ADHD-200 dataset, we developed a Support Vector Machine (SVM) model to classify ADHD patients from typically developing controls (TDCs), using the regional brain volumes as predictors. Conventionally, the volume of a brain region was considered to be an anatomical feature and quantified using structural magnetic resonance images. One major contribution of the present study was that we had initially proposed to measure the regional brain volumes using fMRI images...
2017: Frontiers in Computational Neuroscience
https://www.readbyqxmd.com/read/28943731/multi-source-multi-target-dictionary-learning-for-prediction-of-cognitive-decline
#4
Jie Zhang, Qingyang Li, Richard J Caselli, Paul M Thompson, Jieping Ye, Yalin Wang
Alzheimer's Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information...
June 2017: Information Processing in Medical Imaging: Proceedings of the ... Conference
https://www.readbyqxmd.com/read/28941131/promoting-sketching-in-introductory-geoscience-courses-cogsketch-geoscience-worksheets
#5
Bridget Garnier, Maria Chang, Carol Ormand, Bryan Matlen, Basil Tikoff, Thomas F Shipley
Research from cognitive science and geoscience education has shown that sketching can improve spatial thinking skills and facilitate solving spatially complex problems. Yet sketching is rarely implemented in introductory geosciences courses, due to time needed to grade sketches and lack of materials that incorporate cognitive science research. Here, we report a design-centered, collaborative effort, between geoscientists, cognitive scientists, and artificial intelligence (AI) researchers, to characterize spatial learning challenges in geoscience and to design sketch activities that use a sketch-understanding program, CogSketch...
September 23, 2017: Topics in Cognitive Science
https://www.readbyqxmd.com/read/28940395/delay-discounting-as-impaired-valuation-delayed-rewards-in-an-animal-obesity-model
#6
David P Jarmolowicz, Jennifer L Hudnall, Luanne Hale, Stephen C Fowler, Marco Bortolato, Shea M Lemley, Michael J Sofis
Obesity is a major public health problem, which, like many forms of addiction, is associated with an elevated tendency to choose smaller immediate rather than larger delayed rewards, a response pattern often referred to as excessive delay discounting. Although some accounts of delay discounting conceptualize this process as impulsivity (placing the emphasis on overvaluing the smaller immediate reward), others have conceptualized delay discounting as an executive function (placing the emphasis on delayed rewards failing to retain their value)...
September 2017: Journal of the Experimental Analysis of Behavior
https://www.readbyqxmd.com/read/28939535/reading-difficulties-and-the-pediatric-ophthalmologist
#7
EDITORIAL
Sheryl M Handler, Walter M Fierson
Approximately 20% of children have dyslexia, a language-based reading disability. A variation in language processing in the brain leads to a deficit in phonological (auditory) processing, which leads to problems in learning to read, write, and spell. Myths continue to exist regarding dyslexia and vision, and although eye and vision problems may coexist with dyslexia, they are not more prevalent than in the general population. Rarely vision problems may make reading at near very difficult and may masquerade as a learning problem or attention deficit disorder/attention deficit hyperactivity disorder...
September 19, 2017: Journal of AAPOS: the Official Publication of the American Association for Pediatric Ophthalmology and Strabismus
https://www.readbyqxmd.com/read/28937281/tracking-by-detection-of-surgical-instruments-in-minimally-invasive-surgery-via-the-convolutional-neural-network-deep-learning-based-method
#8
Zijian Zhao, Sandrine Voros, Ying Weng, Faliang Chang, Ruijian Li
BACKGROUND: Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. METHODS: A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one...
September 22, 2017: Computer Assisted Surgery (Abingdon, England)
https://www.readbyqxmd.com/read/28937117/gender-differences-in-dental-students-professional-expectations-and-attitudes-a-qualitative-study
#9
M da Graça Kfouri, S T Moysés, M C L Gabardo, S J Moysés
Introduction With the significant increase of women in dentistry, the profile of the dental professional has been altered.Aim To investigate the discourses of future dental surgeons, of both genders, from public and private universities of Curitiba, Paraná, Brazil, to detect whether gender profile differences can influence training and intended future practice.Methods The problem is approached using a qualitative design, with the strategy of collective interviews in focus groups followed by a discourse analysis...
September 22, 2017: British Dental Journal
https://www.readbyqxmd.com/read/28936917/scalable-collaborative-targeted-learning-for-high-dimensional-data
#10
Cheng Ju, Susan Gruber, Samuel D Lendle, Antoine Chambaz, Jessica M Franklin, Richard Wyss, Sebastian Schneeweiss, Mark J van der Laan
Robust inference of a low-dimensional parameter in a large semi-parametric model relies on external estimators of infinite-dimensional features of the distribution of the data. Typically, only one of the latter is optimized for the sake of constructing a well-behaved estimator of the low-dimensional parameter of interest. Optimizing more than one of them for the sake of achieving a better bias-variance trade-off in the estimation of the parameter of interest is the core idea driving the general template of the collaborative targeted minimum loss-based estimation procedure...
January 1, 2017: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/28935341/conduct-problems-in-youth-and-the-rdoc-approach-a-developmental-evolutionary-based-view
#11
REVIEW
Peter Fonagy, Patrick Luyten
Problems related to aggression in young people are traditionally subsumed under the header of conduct problems, which include conduct disorder and oppositional defiant disorder. Such problems in children and adolescents are an important societal and mental health problem. In this paper we present an evolutionarily informed developmental psychopathology view of conduct problems inspired by the NIMH Research Domain Criteria (RDoC) initiative. We assume that while there are many pathways to conduct problems, chronic or temporary impairments in the domain of social cognition or mentalizing are a common denominator...
September 8, 2017: Clinical Psychology Review
https://www.readbyqxmd.com/read/28934917/sparse-supervised-classification-methods-predict-and-characterize-nanomaterial-exposures-independent-markers-of-mwcnt-exposures
#12
Naveena Yanamala, Marlene S Orandle, Vamsi K Kodali, Lindsey Bishop, Patti C Zeidler-Erdely, Jenny R Roberts, Vincent Castranova, Aaron Erdely
Recent experimental evidence indicates significant pulmonary toxicity of multiwalled carbon nanotubes (MWCNTs), such as inflammation, interstitial fibrosis, granuloma formation, and carcinogenicity. Although numerous studies explored the adverse potential of various CNTs, their comparability is often limited. This is due to differences in administered dose, physicochemical characteristics, exposure methods, and end points monitored. Here, we addressed the problem through sparse classification method, a supervised machine learning approach that can reduce the noise contained in redundant variables for discriminating among MWCNT-exposed and MWCNT-unexposed groups...
January 1, 2017: Toxicologic Pathology
https://www.readbyqxmd.com/read/28934641/graph-construction-using-adaptive-local-hybrid-coding-scheme
#13
Fadi Dornaika, Mahdi Tavassoli Kejani, Alireza Bosaghzadeh
It is well known that dense coding with local bases (via Least Square coding schemes) can lead to large quantization errors or poor performances of machine learning tasks. On the other hand, sparse coding focuses on accurate representation without taking into account data locality due to its tendency to ignore the intrinsic structure hidden among the data. Local Hybrid Coding (LHC) (Xiang et al., 2014) was recently proposed as an alternative to the sparse coding scheme that is used in Sparse Representation Classifier (SRC)...
August 24, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28934254/deep-reconstruction-model-for-dynamic-pet-images
#14
Jianan Cui, Xin Liu, Yile Wang, Huafeng Liu
Accurate and robust tomographic reconstruction from dynamic positron emission tomography (PET) acquired data is a difficult problem. Conventional methods, such as the maximum likelihood expectation maximization (MLEM) algorithm for reconstructing the activity distribution-based on individual frames, may lead to inaccurate results due to the checkerboard effect and limitation of photon counts. In this paper, we propose a stacked sparse auto-encoder based reconstruction framework for dynamic PET imaging. The dynamic reconstruction problem is formulated in a deep learning representation, where the encoding layers extract the prototype features, such as edges, so that, in the decoding layers, the reconstructed results are obtained through a combination of those features...
2017: PloS One
https://www.readbyqxmd.com/read/28933027/learning-directed-acyclic-graphs-from-large-scale-genomics-data
#15
Fabio Nikolay, Marius Pesavento, George Kritikos, Nassos Typas
In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best...
September 20, 2017: EURASIP Journal on Bioinformatics & Systems Biology
https://www.readbyqxmd.com/read/28932135/effectiveness-of-two-interactive-educational-methods-to-teach-tobacco-cessation-counseling-for-senior-dental-students
#16
Mina Ahmadian, Mohammad Reza Khami, Arezoo Ebn Ahamdi, Samaneh Razeghi, Reza Yazdani
OBJECTIVE: Nowadays, one of the major health problems in many countries is tobacco use. Dental professionals are in a unique position to promote smoking cessation since they have the opportunity for regular interaction with their patients. The purpose of the present study was to compare the effectiveness of two educational methods to teach tobacco cessation counseling (TCC) in dental practice for senior dental students. MATERIALS AND METHODS: In this interventional study, 93 eligible senior dental students from two dental schools in Tehran, Iran were randomly divided into two groups...
July 2017: European Journal of Dentistry
https://www.readbyqxmd.com/read/28932103/a-modified-mean-gray-wolf-optimization-approach-for-benchmark-and-biomedical-problems
#17
Narinder Singh, S B Singh
A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant...
2017: Evolutionary Bioinformatics Online
https://www.readbyqxmd.com/read/28930064/increasing-alcohol-taxes-analysis-of-case-studies-from-illinois-maryland-and-massachusetts
#18
Rebecca L Ramirez, David H Jernigan
OBJECTIVE: The effectiveness of alcohol taxes in reducing excessive alcohol consumption and related problems is well established in research, yet increases in U.S. state alcohol taxes are uncommon. This study examined how alcohol tax increases occurred recently in three U.S. states, what public health's role was, and what can be learned from those experiences. METHOD: Review of available documentation and news media content analysis provided context and, along with snowball sampling, helped identify proponents, opponents, and neutral parties in each state...
September 2017: Journal of Studies on Alcohol and Drugs
https://www.readbyqxmd.com/read/28927941/gaming-the-system-creation-of-a-random-case-generating-game-for-use-in-morning-report
#19
Pallavi Kamra, Emily C Borman-Shoap, Lei Zhang, Michael B Pitt
BACKGROUND: Case-based morning reports are a staple of residency education. Little is known about the role of game-based learning in facilitating case-based discussions. OBJECTIVES: Compare an educational game that can be used for creating impromptu case-based sessions to traditional morning report. METHODS: We created a game called Differential Diagnosis Slot Machine, which allows participants to quickly generate theoretical cases for discussion...
September 16, 2017: Academic Pediatrics
https://www.readbyqxmd.com/read/28923375/the-feldenkrais-method-improves-functioning-and-body-balance-in-people-with-intellectual-disability-in-supported-employment-a-randomized-clinical-trial
#20
Jon Torres-Unda, Vanesa Polo, Iratxe Dunabeitia, Iraia Bidaurrazaga-Letona, María García-Gil, Ana Rodriguez-Larrad, Jon Irazusta
Loss of functioning and age-related health problems tend to appear earlier in individuals with intellectual disability (ID) than in their non-disabled peers. The Feldenkrais method (FM) is a movement-based form of learning that enhances body balance and physical functioning. We carried out an intervention based on Awareness Through Movement, a form of the FM. Thirty-two middle-aged (48.94±6.01years old) adults with ID who were in supported employment were recruited and randomly assigned to the experimental group (EG) or control group (CG)...
September 15, 2017: Research in Developmental Disabilities
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