P132 Student Perspectives of Service-Learning in a Community Nutrition Course
To evaluate how a service-learning component in a Community Nutrition course changed student perceptions of the benefits of service-learning. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Georgianna Mann Source Type: research

P130 Improving Student Engagement and Learning Environment Through Formative Assessment of an Online, Advanced Nutrition Course
To conduct formative assessment to improve online learning environment for an advanced nutrition course. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Zubaida Qamar Source Type: research

P125 Assessment of Active Learning Techniques and Experiential Learning Coursework on Dietetic Student's Perceptions of Learning
To assess the role of experiential/service learning and active student learning approaches on students' perceptions of the experiences and approaches. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Karen Gordon Source Type: research

P110 Adoption of an Electronic Textbook with Inclusive Access and Adaptive Learning Reduces DFWI Rate in an Online Introductory Nutrition Course
To determine the impact of switching from a hard copy to an electronic textbook with inclusive access and adaptive learning experiences on the drop, fail, withdraw, incomplete (DFWI) rate in an online undergraduate introductory nutrition course. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Cheryl L.H. Armstrong Source Type: research

P111 Australian Nutrition and Dietetic Students ’ Familiarity with Dimensions of Sustainability
There is increased focus on integrating sustainability in University level nutrition and dietetic curriculum, however developing relevant learning activities and assessment can be challenging due to varied experiences and views of this topic. Understanding the student perspective can provide interesting and important insights which may identify current curriculum needs and student knowledge gaps. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Sarah Burkhart, Maher Judith, Michele Verdonck, Theresa Ashford Source Type: research

P112 Can Food-Based Learning Activities Improve Head Start Preschool Children's Vegetable Intake?
Low vegetable consumption is often observed among low-resource families who are also at risk for overweight/obesity. Repeated exposure to vegetables in the preschool setting has been shown to increase vegetable intake and decrease neophobia among children. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Jocelyn Bayles, Sarah Burkholder, Stephanie Jilcott Pitts, Archana Hedge, Virginia Stage Source Type: research

P104 Guided Inquiry-Based Learning and the Date Label/Milk Waste Conundrum
Review an innovative active learning activity with a self-reflecting essay that connected an everyday food shopping experience of reading a date label to decisions about milk drinkability. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Priscilla Connors Source Type: research

P89 The Impact of Digital Learning on Child Care Providers Regarding the Implementation of CACFP Meal Pattern
With the release of 2017 United State Department of Agriculture (USDA)/Child and Adult Care Food Program (CACFP) meal pattern, states need to provide training and technical assistance to all Child Care Providers (CCPs) who participate in CACFP to ensure that healthy foods are served to children during mealtime in order to improve early childhood dietary quality and health outcomes. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Zainab Rida, Christy Burger, Alian Kasabian Source Type: research

P75 Improving Teacher Knowledge and Self-Efficacy to Promote Healthy Eating and Physical Activity in the Child Care Setting
Obesity prevention should begin in early childhood, when children are learning nutrition and physical activity behaviors. Early childhood education (ECE) teachers play a key role in obesity prevention. Teachers ’ ability to encourage healthy habits is related to their knowledge and self-efficacy related to obesity prevention strategies. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Caree Cotwright, Diane Bales, Joanna Akin, Jung Sun Lee Source Type: research

P68 FSU Cooks: Culinary Nutrition Workshops Help Participants Learn About Food, Cook, and Eat!
FSU Cooks: Learn.Cook.Eat was developed by the Food and Nutrition Department (FND) at Framingham State University (FSU). The purpose of the program is to provide an educational environment focused on food and culinary literacy. Participants learn about food, participate in hand-on cooking, and eat their creations. The aim of the pilot was to assess the feasibility of offering the program to community members. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Catherine Wickham, Jerusha Nelson-Peterman, Ann Johnson Source Type: research

P24 Exploration of Graduate Students ’ Experience in a Flipped Course Using Learning Reflections
To evaluate graduate students ’ experience in a flipped advanced metabolism course using periodic learning reflections. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Rachel L. Vollmer, Teresa Drake Source Type: research

FP6 Supporting Healthy Habits in Childcare with Online Trainings for CACFP Participants
To develop interactive and engaging online trainings for CACFP (Child and Adult Care Food Program) participants, based on adult learning principles and instructional strategy, including audience analysis, and formative evaluation of knowledge gained. The modules support healthy habits in childcare homes and centers. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Patti Delger, Bryan Bauer, Tiffany Morgan Source Type: research

NP5 Salud Para Usted y Su Familia [Health for You and Your Family]: Integration of Research, Education and Extension to Promote Healthier Mexican-Heritage Families
We describe research (stepped wedge cluster randomized controlled trial [SWCRCT] of father-focused, family-centered program), education (experiential learning and innovative teaching), and extension (promotora-led charlas [chats/talks]) components. (Source: Journal of Nutrition Education and Behavior)
Source: Journal of Nutrition Education and Behavior - July 1, 2019 Category: Nutrition Authors: Joseph Sharkey, Renee Umstattd Meyer, Cassandra Johnson, Luis Gomez, Luz Martinez, Elva Beltran, Tomas Johanson Source Type: research

A test of the variability vs. specificity hypotheses in the retention of a motor skill.
Abstract The variability of practice hypothesis suggests that practicing with task variations enhances motor learning (Schmidt, 1975). However, in tasks with only a single criterion goal to be learned, the evidence that variable practice enhances retention of this criterion task compared to constant practice (i.e. practicing without task variations) is somewhat mixed. We seek to address this question in a registered report by pre-registering the hypothesis, using a larger sample size, and using a Bayesian approach to directly quantify the evidence for the hypothesis (instead of conventional null hypothesis signifi...
Source: Human Movement Science - July 1, 2019 Category: Neurology Authors: Ranganathan R Tags: Hum Mov Sci Source Type: research

An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution.
Abstract Various approaches have been proposed to model PM2.5 in the recent decade, with satellite-derived aerosol optical depth, land-use variables, chemical transport model predictions, and several meteorological variables as major predictor variables. Our study used an ensemble model that integrated multiple machine learning algorithms and predictor variables to estimate daily PM2.5 at a resolution of 1 km × 1 km across the contiguous United States. We used a generalized additive model that accounted for geographic difference to combine PM2.5 estimates from neural network, random forest, and gradi...
Source: Environment International - July 1, 2019 Category: Environmental Health Authors: Di Q, Amini H, Shi L, Kloog I, Silvern R, Kelly J, Sabath MB, Choirat C, Koutrakis P, Lyapustin A, Wang Y, Mickley LJ, Schwartz J Tags: Environ Int Source Type: research

Using Bloom's Taxonomy Matrix to Reach Higher-Level Learning Objectives.
PMID: 31270262 [PubMed - in process] (Source: Radiologic Technology)
Source: Radiologic Technology - July 1, 2019 Category: Radiology Authors: Spence B Tags: Radiol Technol Source Type: research

A role for metamemory in cognitive offloading.
Abstract Cognitive offloading refers to our reliance on the external environment in order to reduce cognitive demand. For instance, people write notes on paper or smartphones in order not to forget shopping lists or upcoming appointments. A plausible hypothesis is that such offloading relies on metamemory - our confidence in our future memory performance. However, this hypothesis has not been directly tested, and it remains unclear when and how people use external sources to aid their encoding and retrieval of information. In four experiments, here we asked participants to learn word pairs and decide whether to of...
Source: Cognition - July 1, 2019 Category: Neurology Authors: Hu X, Luo L, Fleming SM Tags: Cognition Source Type: research

Effects of explanation on children's question asking.
Abstract The capacity to search for information effectively by asking informative questions is crucial for self-directed learning and develops throughout the preschool years and beyond. We tested the hypothesis that explaining observations in a given domain prepares children to ask more informative questions in that domain, and that it does so by promoting the identification of features that apply to multiple objects, thus supporting more effective questions. Across two experiments, 4- to 7-year-old children (N  = 168) were prompted to explain observed evidence or to complete a control task prior to a 20-quest...
Source: Cognition - July 1, 2019 Category: Neurology Authors: Ruggeri A, Xu F, Lombrozo T Tags: Cognition Source Type: research

Weighted Transfer Learning for Improving Motor Imagery-Based Brain–Computer Interface
One of the major limitations of motor imagery (MI)-based brain–computer interface (BCI) is its long calibration time. Due to between sessions/subjects variations in the properties of brain signals, typically, a large amount of training data needs to be collected at the beginning of each session to calibrate the parameters of the BCI system for the target user. In this paper, we propose a novel transfer learning approach on the classification domain to reduce the calibration time without sacrificing the classification accuracy of MI-BCI. Thus, when only few subject-specific trials are available for training, the estim...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - July 1, 2019 Category: Neuroscience Source Type: research

A Mechatronic System for Studying Energy Optimization During Walking
A general principle of human movement is that our nervous system is able to learn optimal coordination strategies. However, how our nervous system performs this optimization is not well understood. Here we design, build, and test a mechatronic system to probe the algorithms underlying the optimization of energetic cost in walking. The system applies controlled fore-aft forces to a hip-belt worn by a user, decreasing their energetic cost by pulling forward, or increasing it by pulling backward. The system controls the forces, and thus energetic cost as a function of how the user is moving. In testing, we found that the syst...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - July 1, 2019 Category: Neuroscience Source Type: research

From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes
There has been increased effort to understand the neurophysiological effects of concussion aimed to move diagnosis and identification beyond current subjective behavioral assessments that suffer from poor sensitivity. Recent evidence suggests that event-related potentials (ERPs) measured with electroencephalography (EEG) are persistent neurophysiological markers of past concussions. However, as such evidence is limited to group-level analyzes, the extent to which they enable concussion detection at the individual-level is unclear. One promising avenue of research is the use of machine learning to create quantitative predic...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - July 1, 2019 Category: Neuroscience Source Type: research

Drug target group prediction with multiple drug networks.
CONCLUSION: Tenfold cross-validation yielded the accuracy of 0.839, exact match of 0.816 and hamming loss of 0.037, indicating the good performance of the model. The contribution of each network was also analyzed. Furthermore, the network model with multiple networks was superior to that with certain single network and classic model, indicating the superiority of the proposed model. PMID: 31267864 [PubMed - as supplied by publisher] (Source: Combinatorial Chemistry and High Throughput Screening)
Source: Combinatorial Chemistry and High Throughput Screening - July 1, 2019 Category: Chemistry Authors: Che J, Chen L, Guo ZH, Wang S, Aorigele Tags: Comb Chem High Throughput Screen Source Type: research

Positional encoding in cotton-top tamarins (Saguinus oedipus).
Abstract Strategies used in artificial grammar learning can shed light into the abilities of different species to extract regularities from the environment. In the A(X)nB rule, A and B items are linked, but assigned to different positional categories and separated by distractor items. Open questions are how widespread is the ability to extract positional regularities from A(X)nB patterns, which strategies are used to encode positional regularities and whether individuals exhibit preferences for absolute or relative position encoding. We used visual arrays to investigate whether cotton-top tamarins (Saguinusoedipus...
Source: Animal Cognition - July 1, 2019 Category: Zoology Authors: Versace E, Rogge JR, Shelton-May N, Ravignani A Tags: Anim Cogn Source Type: research

Artificial intelligence: its applications in reproductive medicine and the assisted reproductive technologies
At its core, artificial intelligence (AI) is “a partnership between man and machine” (Ginni Rometty, IBM CEO). The embodiment of AI is a computer program that can learn to execute tasks involving forms of intelligence normally ascribed to humans. How well a computer will be able to emulate or exceed humans is the essential question driving AI technology. (Source: Fertility and Sterility)
Source: Fertility and Sterility - July 1, 2019 Category: Reproduction Medicine Authors: Nikica Zaninovic, Olivier Elemento, Zev Rosenwaks Tags: Inklings Source Type: research

Public views regarding the responsibility of patients, clinicians, and institutions to participate in research in the United States.
CONCLUSIONS: Efforts to justify and develop a robust learning health system in an ethically acceptable fashion need to take these findings into account. PMID: 31256635 [PubMed - as supplied by publisher] (Source: Clinical Trials)
Source: Clinical Trials - July 1, 2019 Category: Research Authors: Weinfurt KP, Lin L, Sugarman J Tags: Clin Trials Source Type: research

Confused or curious? Openness/intellect predicts more positive interest-confusion relations.
Abstract Open people show greater interest in situations that are complex, novel, and difficult to understand-situations that may also be experienced as confusing. Here we investigate the possibility that openness/intellect is centrally characterized by more positive relations between interest and confusion. Interest and confusion are key states experienced during engagement with information and learning. However, little is known about the within-person relation between them, let alone individual differences in this relation. We tested our hypotheses by making use of different paradigms, stimuli, and participants....
Source: Journal of Personality and Social Psychology - July 1, 2019 Category: Psychiatry & Psychology Authors: Fayn K, Silvia PJ, Dejonckheere E, Verdonck S, Kuppens P Tags: J Pers Soc Psychol Source Type: research

Neural signatures of conditioning, extinction learning, and extinction recall in posttraumatic stress disorder: a meta-analysis of functional magnetic resonance imaging studies.
CONCLUSION: Findings from this metanalysis suggest that PTSD is characterized by increased activation in areas related to salience and threat, and lower activation in the thalamus, a key relay hub between subcortical areas. If replicated, these fear network alterations may serve as objective diagnostic markers for PTSD, and potential targets for novel treatment development, including pharmacological and brain stimulation interventions. Future longitudinal studies are needed to examine whether these observed network alteration in PTSD are the cause or the consequence of PTSD. PMID: 31258096 [PubMed - as supplied by pub...
Source: Psychological Medicine - July 1, 2019 Category: Psychiatry Authors: Suarez-Jimenez B, Albajes-Eizagirre A, Lazarov A, Zhu X, Harrison BJ, Radua J, Neria Y, Fullana MA Tags: Psychol Med Source Type: research

Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics.
CONCLUSIONS: Developing an aneurysm rupture prediction model that applies to Japanese and Finnish aneurysms requires including data from these two cohorts for model training, as well as interaction terms between patient population and the other variables in the model. When including this information, the performance of such a model with Japanese and Finnish data is close to its performance with US or European data. These results suggest that population-specific differences determine how hemodynamics and shape associate with rupture risk in intracranial aneurysms. PMID: 31261120 [PubMed - in process] (Source: Neurosurgical Focus)
Source: Neurosurgical Focus - July 1, 2019 Category: Neurosurgery Authors: Detmer FJ, Hadad S, Chung BJ, Mut F, Slawski M, Juchler N, Kurtcuoglu V, Hirsch S, Bijlenga P, Uchiyama Y, Fujimura S, Yamamoto M, Murayama Y, Takao H, Koivisto T, Frösen J, Cebral JR Tags: Neurosurg Focus Source Type: research

Agent ‐based models of inflammation in translational systems biology: A decade later
This article is categorized under: Translational, Genomic, and Systems Medicine> Translational Medicine Models of Systems Properties and Processes> Mechanistic Models Models of Systems Properties and Processes> Organ, Tissue, and Physiological Models Models of Systems Properties and Processes> Organismal Models (Source: Wiley Interdisciplinary Reviews: Systems Biology and Medicine)
Source: Wiley Interdisciplinary Reviews: Systems Biology and Medicine - July 1, 2019 Category: Biomedical Science Authors: Yoram Vodovotz, Gary An Tags: UPDATE Source Type: research

AANA lab courses offer attendees a personalized learning experience like no other. Our hands-on cadaveric training courses utilize the latest virtual reality simulation technology and expert knowledge from leading surgeons to ensure attendees walk away with the refined skills needed to improve patient outcomes. Find your course today at aana.org/labcourses. (Source: Arthroscopy - Journal of Arthroscopic and Related Surgery)
Source: Arthroscopy - Journal of Arthroscopic and Related Surgery - July 1, 2019 Category: Surgery Tags: Announcements Source Type: research

Radiological –pathological correlation of the British Thyroid Association ultrasound classification of thyroid nodules: a real-world validation study
To evaluate the real-world performance of the British Thyroid Association (BTA) U classification, specifically focusing on radiology –pathology correlation and to glean learning points. (Source: Clinical Radiology)
Source: Clinical Radiology - July 1, 2019 Category: Radiology Authors: H. Al-Chalabi, S. Karthik, S. Vaidyanathan Source Type: research

Cover Image
The cover image is based on the Original ResearchToward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning by Wei Zhao et al., DOI:10.1002/cam4.2233. Design Credit: Ming Li, Wei Zhao, Jiancheng Yang and Ye Ge. (Source: Cancer Medicine)
Source: Cancer Medicine - July 1, 2019 Category: Cancer & Oncology Authors: Wei Zhao, Jiancheng Yang, Bingbing Ni, Dexi Bi, Yingli Sun, Mengdi Xu, Xiaoxia Zhu, Cheng Li, Liang Jin, Pan Gao, Peijun Wang, Yanqing Hua, Ming Li Tags: COVER IMAGE Source Type: research

Biosensing-by-Learning Direct Targeting Strategy for Enhanced Tumor Sensitization
The objective function may be resulted from a passive phenomenon such as reduced blood flow or increased kurtosis of microvasculature due to tumor angiogenesis; otherwise, the objective function may involve an active phenomenon such as the fibrin formed during the coagulation cascade activated by tumor-targeted “activator” nanoparticles. Subsequently, the DTS can be interpreted from the iterative optimization perspective: guess inputs (i.e., swarms of nanoswimmers) are continuously updated according to the gradient of the objective function in order to find the optimum (i.e., tumor) by moving through the domain...
Source: IEE Transactions on NanoBioscience - July 1, 2019 Category: Nanotechnology Source Type: research

Type-2 Fuzzy PCA Approach in Extracting Salient Features for Molecular Cancer Diagnostics and Prognostics
Machine learning is becoming a powerful tool for cancer diagnosis and prognosis based on classification using high dimensional molecular data. However, extracting classification features from high-dimensional datasets remains a challenging problem. Principal component analysis (PCA) is a widely used method for dimensionality reduction. However, it is well-known that PCA and most PCA-based feature extraction methods are sensitive to noise, which may affect the accuracy of the subsequent classification. To address this problem, here we have proposed a robust fuzzy principal component analysis (PCA) with interval type-2 (IT-2...
Source: IEE Transactions on NanoBioscience - July 1, 2019 Category: Nanotechnology Source Type: research

Incorporating User Generated Content for Drug Drug Interaction Extraction Based on Full Attention Mechanism
It is crucial for doctors to fully understand the interaction between drugs in prescriptions, especially when a patient takes multiple medications at the same time during treatment. The purpose of drug drug interaction (DDI) extraction is to automatically obtain the interaction between drugs from biomedical literature. Current state-of-the-art approaches for DDI extraction task are based on artificial intelligence and natural language processing. While such existing DDI extraction methods can provide more knowledge and enhance the performance through external resources such as biomedical databases or ontologies, due to the...
Source: IEE Transactions on NanoBioscience - July 1, 2019 Category: Nanotechnology Source Type: research

Learning to Predict Drug Target Interaction From Missing Not at Random Labels
The prediction of Drug-Target Interaction (DTI) is an important research direction in bioinformatics as it greatly shortens the development cycle of new drugs. State-of-the-art computational methods for DTI prediction adopt a binary classification framework. The supervision is incomplete, i.e. only a small amount of DTIs are known and treated as positive instances, while the rest are unknown and treated as negative. Two severe problems occur in such a framework: (1) the number of negative samples is overwhelming and (2) a negative label cannot rule out the possibility of a positive drug-target interaction. In this paper, w...
Source: IEE Transactions on NanoBioscience - July 1, 2019 Category: Nanotechnology Source Type: research

Serendipity—A Machine-Learning Application for Mining Serendipitous Drug Usage From Social Media
Serendipitous drug usage refers to the unexpected relief of comorbid diseases or symptoms when taking medication for a different known indication. Historically, serendipity has contributed significantly to identifying many new drug indications. If patient-reported serendipitous drug usage in social media could be computationally identified, it could help generate and validate drug-repositioning hypotheses. We investigated deep neural network models for mining serendipitous drug usage from social media. We used the word2vec algorithm to construct word-embedding features from drug reviews posted in a WebMD patient forum. We ...
Source: IEE Transactions on NanoBioscience - July 1, 2019 Category: Nanotechnology Source Type: research

Chinese Clinical Named Entity Recognition Using Residual Dilated Convolutional Neural Network With Conditional Random Field
Clinical named entity recognition (CNER) is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on recurrent neural networks (RNNs), which maintain a vector of hidden activations that are propagated through time, thus causing too much time to train models. In this paper, we propose a residual dilated convolutional neural network with the conditional random field (RD-CNN-CRF) for the Chinese CNER, which makes the model asynchronous in computation and thus speeding up the training pe...
Source: IEE Transactions on NanoBioscience - July 1, 2019 Category: Nanotechnology Source Type: research

Phy-PMRFI: Phylogeny-Aware Prediction of Metagenomic Functions Using Random Forest Feature Importance
High-throughput sequencing techniques have accelerated functional metagenomics studies through the generation of large volumes of omics data. The integration of these data using computational approaches is potentially useful for predicting metagenomic functions. Machine learning (ML) models can be trained using microbial features which are then used to classify microbial data into different functional classes. For example, ML analyses over the human microbiome data has been linked to the prediction of important biological states. For analysing omics data, integrating abundance count of taxonomical features with their biolo...
Source: IEE Transactions on NanoBioscience - July 1, 2019 Category: Nanotechnology Source Type: research

The Physician ’s Physician
Psychiatrists have valuable training, knowledge, and experience to serve as champions for physician health. The prevalence of physician burnout, suicide, and depression negatively affects the health care system at a critical time when the country faces a physician shortage, increasing costs, and a push toward higher quality of care. Psychiatrists are in prime position to serve as the “Physician’s Physician” and lead their organizations to increase awareness, build capacity, and drive cultural change. New leadership opportunities exist for psychiatrists, including the role of chief wellness officer, servin...
Source: The Psychiatric Clinics of North America - July 1, 2019 Category: Psychiatry Authors: Keisuke Nakagawa, Peter M. Yellowlees Source Type: research

Ea-GANs: Edge-Aware Generative Adversarial Networks for Cross-Modality MR Image Synthesis
Magnetic resonance (MR) imaging is a widely used medical imaging protocol that can be configured to provide different contrasts between the tissues in human body. By setting different scanning parameters, each MR imaging modality reflects the unique visual characteristic of scanned body part, benefiting the subsequent analysis from multiple perspectives. To utilize the complementary information from multiple imaging modalities, cross-modality MR image synthesis has aroused increasing research interest recently. However, most existing methods only focus on minimizing pixel/voxel-wise intensity difference but ignore the text...
Source: IEE Transactions on Medical Imaging - July 1, 2019 Category: Biomedical Engineering Source Type: research

A Machine Learning Approach for Classifying Ischemic Stroke Onset Time From Imaging
Current clinical practice relies on clinical history to determine the time since stroke (TSS) onset. Imaging-based determination of acute stroke onset time could provide critical information to clinicians in deciding stroke treatment options, such as thrombolysis. The patients with unknown or unwitnessed TSS are usually excluded from thrombolysis, even if their symptoms began within the therapeutic window. In this paper, we demonstrate a machine learning approach for TSS classification using routinely acquired imaging sequences. We develop imaging features from the magnetic resonance (MR) images and train machine learning ...
Source: IEE Transactions on Medical Imaging - July 1, 2019 Category: Biomedical Engineering Source Type: research

MR Image Reconstruction Using Deep Density Priors
Algorithms for magnetic resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data. Deep learning (DL) provides a powerful framework for extracting such information from existing image datasets, through learning, and then using it for reconstruction. Leveraging this, recent methods employed DL to learn mappings from undersampled to fully sampled images using paired datasets, including undersampled and corresponding fully sampled images, integrating prior knowledge implicitly. In this letter, we propose an alternative approach that learns the probabili...
Source: IEE Transactions on Medical Imaging - July 1, 2019 Category: Biomedical Engineering Source Type: research

Sensors, Vol. 19, Pages 2919: Synthesizing Depth Hand Images with GANs and Style Transfer for Hand Pose Estimation
Wendi Cai Hand pose estimation is a critical technology of computer vision and human-computer interaction. Deep-learning methods require a considerable amount of tagged data. Accordingly, numerous labeled training data are required. This paper aims to generate depth hand images. Given a ground-truth 3D hand pose, the developed method can generate depth hand images. To be specific, a ground truth can be 3D hand poses with the hand structure contained, while the synthesized image has an identical size to that of the training image and a similar visual appearance to the training set. The developed method, inspired by the ...
Source: Sensors - July 1, 2019 Category: Biotechnology Authors: Wangyong He Zhongzhao Xie Yongbo Li Xinmei Wang Wendi Cai Tags: Article Source Type: research

Sensors, Vol. 19, Pages 2918: Laplacian Eigenmaps Network-Based Nonlocal Means Method for MR Image Denoising
Zhang Magnetic resonance (MR) images are often corrupted by Rician noise which degrades the accuracy of image-based diagnosis tasks. The nonlocal means (NLM) method is a representative filter in denoising MR images due to its competitive denoising performance. However, the existing NLM methods usually exploit the gray-level information or hand-crafted features to evaluate the similarity between image patches, which is disadvantageous for preserving the image details while smoothing out noise. In this paper, an improved nonlocal means method is proposed for removing Rician noise in MR images by using the refined similar...
Source: Sensors - July 1, 2019 Category: Biotechnology Authors: Houqiang Yu Mingyue Ding Xuming Zhang Tags: Article Source Type: research

IJERPH, Vol. 16, Pages 2325: Case Study: How Horses Helped a Teenager with Autism Make Friends and Learn How to Work
n I was born in 1947 and had autism with speech delay until age four. I am now a college professor of animal science. Horse activities enabled me to make friends through a shared interest in horses. This paper describes the benefits that I experienced from working with horses and my friendships and work skills. A close friendship developed with another student through both riding and horse craft projects. Keeping employment is a serious problem for many people with Autism Spectrum Disorder (ASD). The responsibility of caring for horses and cleaning stalls every day taught me good work skills. My experiences suggest tha...
Source: International Journal of Environmental Research and Public Health - July 1, 2019 Category: Environmental Health Authors: Temple Grandin Tags: Article Source Type: research

Implementing the Movement-Oriented Practising Model (MPM) in physical education: empirical findings focusing on student learning
. (Source: Physical Education and Sport Pedagogy)
Source: Physical Education and Sport Pedagogy - July 1, 2019 Category: Sports Medicine Authors: R. Lindgren D. Barker Source Type: research

Surgical Treatment for FAI: Arthroscopic and Open Techniques for Osteoplasty
AbstractPurpose of ReviewTo review the relevant literature and techniques regarding arthroscopic and open treatment of femoroacetabular impingement (FAI). To discuss both the senior authors ’ preferred method of arthroscopic and open treatment of FAI.Recent FindingsRoutine treatment of FAI has moved away from open techniques and is more focused arthroscopic methods. Arthroscopic treatment of FAI has more recently focused on differing techniques of hip access and capsular management. Open techniques still have a role in FAI, but indications for open management are focused on cases with more severe pathology.SummaryWhi...
Source: Current Reviews in Musculoskeletal Medicine - July 1, 2019 Category: Orthopaedics Source Type: research

The neurologist and artificial intelligence: Titans at crossroads
Venugopalan Y Vishnu, Pulikottil Wilson VinnyAnnals of Indian Academy of Neurology 2019 22(3):264-266 Clinical judgment to reach final diagnosis has remained a challenge since time immemorial. The present times are witness to artificial intelligence (AI) and machine learning programs competing to outperform the seasoned physician in arriving at a differential diagnosis. We discuss here the possible roles of AI in neurology. (Source: Annals of Indian Academy of Neurology)
Source: Annals of Indian Academy of Neurology - July 1, 2019 Category: Neurology Authors: Venugopalan Y Vishnu Pulikottil Wilson Vinny Source Type: research

Impact of opium dependency on clinical and neuropsychological indices of multiple sclerosis patients
AbstractThe aim of this study was to determine the effect of opium on clinical and neuropsychological parameters in multiple sclerosis (MS) patients with substance dependency. A cross-sectional study was conducted on MS patients in Rafsanjan, Iran. Forty opium-addict MS patients (10 males and 30 females) aged between 18 and 50  years were compared with 40 MS patients with no addiction. Word-Pair Learning, Mini-Mental State Examination (MMSE), Wisconsin Card-Sorting Test (WCST), Depression, Anxiety, Expanded Disability Status Scale (EDSS), Fatigue, and the Multiple Sclerosis Functional Composite (MSFC) were measured an...
Source: Neurological Sciences - July 1, 2019 Category: Neurology Source Type: research