Evaluation of student use of videos to support learning in a simulation laboratory course: A perception and analytics approach
ConclusionVideos were reported to support student learning and were valued for a range of learning needs. However, significant differences between student consumption and strategies need to be designed to engage low consumers. (Source: Journal of Investigative and Clinical Dentistry)
Source: Journal of Investigative and Clinical Dentistry - September 27, 2019 Category: Dentistry Authors: Michael G. Botelho Tags: ORIGINAL ARTICLE Source Type: research

Clear skies ahead: optimizing the learning environment for critical thinking from a  qualitative analysis of interviews with expert teachers
DiscussionAn optimal learning environment for critical thinking was actively created by faculty to establish a  safe environment and shared understanding of expectations. Understanding how to produce a conducive learning climate is paramount in teaching essential topics such as critical thinking. These findings have potential utility for faculty development initiatives to optimize the learning environment. (Source: Perspectives on Medical Education)
Source: Perspectives on Medical Education - September 27, 2019 Category: Universities & Medical Training Source Type: research

Toward an Electronic Health Record Leveraged to Learn from Every Complex Patient Encounter: Health Informatics Considerations with Pediatric Intestinal Rehabilitation as a Model
Of the 13.7 million US children with special healthcare needs, many require chronic care of rare or complex conditions.1 With advancements in medical and surgical care, life expectancy among many of these conditions is lengthening, leading to a generation of children with new and unique healthcare needs.2-4 These children are cared for in a system in which gaps and disparities in quality and outcomes abound. It has been shown that children receive less than one-half of recommended routine care. Yet, for populations with complex and rare medical conditions, care recommendations usually are lacking or incomplete due to a lac...
Source: The Journal of Pediatrics - September 27, 2019 Category: Pediatrics Authors: Ethan A. Mezoff, Peter C. Minneci, Richard R. Hoyt, Jeffrey M. Hoffman Tags: Grand Rounds Source Type: research

Elements in scenario ‐based simulation associated with nursing students' self‐confidence and satisfaction: A cross‐sectional study
AbstractAimTo identify elements in scenario ‐based simulation associated with nursing students' satisfaction with the simulation activity and self‐confidence in managing the simulated patient situation. The study will provide insight to improve the use of simulation as a learning strategy.DesignA cross ‐sectional study.MethodThe Student Satisfaction and Self ‐Confidence in Learning scale was used as the outcome measure to identify associations with elements of the Simulation Design Scale and the Educational Practices Questionnaire scale after scenario‐based simulation using patient simulators. First‐year nursin...
Source: Nursing Open - September 27, 2019 Category: Nursing Authors: Camilla Olaussen, Kristin Heggdal, Christine Raaen Tvedt Tags: RESEARCH ARTICLE Source Type: research

Increasing self ‐efficacy and knowledge in carer training: Hispanic versus Caucasian
AbstractAimNurses are teachers to their patients and need to know best practices for diverse families living with dementia. Little is known about Hispanic beliefs around dementia knowledge and self ‐efficacy that may have an impact on the learning situation.DesignA pre ‐/postresearch design was used in this intervention study with a baseline assessment of dementia knowledge and caregiver self‐efficacy and a reassessment at training completion.MethodsInvestigation of education training with two caregiver groups caring for persons with dementia: Caucasian and Hispanic. Convenience sample consisted of 567 Caucasians and...
Source: Nursing Open - September 27, 2019 Category: Nursing Authors: Leisa Easom, Ke Wang, Gayle Alston Tags: RESEARCH ARTICLE Source Type: research

---
Microsurgical Endodontics is a remarkable textbook that highlights current knowledge in contemporary surgical techniques in endodontics. This textbook consists of 12 chapters with detailed text and stunning photography covering all topics related to microsurgical endodontics. Cutting-edge technology allows readers to use an application on their smart devices to access augmented reality videos by hovering over the images. This feature literally makes the illustrations jump off the page, allowing for a more immersive learning experience. (Source: Journal of Endodontics)
Source: Journal of Endodontics - September 27, 2019 Category: Dentistry Authors: Gary Benjamin Tags: Book Review Source Type: research

Sensors, Vol. 19, Pages 4190: Improving Imaging Quality of Real-time Fourier Single-pixel Imaging via Deep Learning
Qun Hao Fourier single pixel imaging (FSPI) is well known for reconstructing high quality images but only at the cost of long imaging time. For real-time applications, FSPI relies on under-sampled reconstructions, failing to provide high quality images. In order to improve imaging quality of real-time FSPI, a fast image reconstruction framework based on deep learning (DL) is proposed. More specifically, a deep convolutional autoencoder network with symmetric skip connection architecture for real time 96 × 96 imaging at very low sampling rates (5–8%) is employed. The network is trained on a l...
Source: Sensors - September 27, 2019 Category: Biotechnology Authors: Saad Rizvi Jie Cao Kaiyu Zhang Qun Hao Tags: Article Source Type: research

Sensors, Vol. 19, Pages 4199: Conditional Artificial Potential Field-Based Autonomous Vehicle Safety Control with Interference of Lane Changing in Mixed Traffic Scenario
Naixue Xiong Car-following is an essential trajectory control strategy for the autonomous vehicle, which not only improves traffic efficiency, but also reduces fuel consumption and emissions. However, the prediction of lane change intentions in adjacent lanes is problematic, and will significantly affect the car-following control of the autonomous vehicle, especially when the vehicle changing lanes is only a connected unintelligent vehicle without expensive and accurate sensors. Autonomous vehicles suffer from adjacent vehicles’ abrupt lane changes, which may reduce ride comfort and increase energy consu...
Source: Sensors - September 27, 2019 Category: Biotechnology Authors: Kai Gao Di Yan Fan Yang Jin Xie Li Liu Ronghua Du Naixue Xiong Tags: Article Source Type: research

Sensors, Vol. 19, Pages 4207: A Shallow Convolutional Learning Network for Classification of Cancers Based on Copy Number Variations
kour Genomic copy number variations (CNVs) are among the most important structural variations. They are linked to several diseases and cancer types. Cancer is a leading cause of death worldwide. Several studies were conducted to investigate the causes of cancer and its association with genomic changes to enhance its management and improve the treatment opportunities. Classification of cancer types based on the CNVs falls in this category of research. We reviewed the recent, most successful methods that used machine learning algorithms to solve this problem and obtained a dataset that was tested by some of these methods...
Source: Sensors - September 27, 2019 Category: Biotechnology Authors: AlShibli Mathkour Tags: Article Source Type: research

IJERPH, Vol. 16, Pages 3628: Ontology-Based Healthcare Named Entity Recognition from Twitter Messages Using a Recurrent Neural Network Approach
Ryu Named Entity Recognition (NER) in the healthcare domain involves identifying and categorizing disease, drugs, and symptoms for biosurveillance, extracting their related properties and activities, and identifying adverse drug events appearing in texts. These tasks are important challenges in healthcare. Analyzing user messages in social media networks such as Twitter can provide opportunities to detect and manage public health events. Twitter provides a broad range of short messages that contain interesting information for information extraction. In this paper, we present a Health-Related Named Entity Recognition (H...
Source: International Journal of Environmental Research and Public Health - September 27, 2019 Category: Environmental Health Authors: Erdenebileg Batbaatar Keun Ho Ryu Tags: Article Source Type: research

On the relationship of machine learning with causal inference
(Source: European Journal of Epidemiology)
Source: European Journal of Epidemiology - September 27, 2019 Category: Epidemiology Source Type: research

Integration of machine learning and pharmacogenomic biomarkers for predicting response to antidepressant treatment: can computational intelligence be used to augment clinical assessments?
Pharmacogenomics,Volume 20, Issue 14, Page 983-988, September 2019. (Source: Future Medicine: Pharmacogenomics)
Source: Future Medicine: Pharmacogenomics - September 27, 2019 Category: Genetics & Stem Cells Authors: Arjun P Athreya Ravishankar Iyer Liewei Wang Richard M Weinshilboum William V Bobo Source Type: research

SOLO-based task to improve self-evaluation and capacity to integrate concepts in first-year physiology students.
Abstract An accurate self-assessment of student work can enhance student learning and subsequently improve academic performance. Instructors can facilitate this process by providing "standards" that students can utilize as feedback when self-evaluating their understanding. Traditional forms of feedback, such as marked assessment tasks, are limited in their ability to serve as standards, as they do not adequately capture variations corresponding to different levels of understanding. To develop a complex understanding in physiology, students have to integrate concepts pertaining to different subcomponents ...
Source: Adv Physiol Educ - September 26, 2019 Category: Universities & Medical Training Authors: Williams MT, Lluka LJ, Meyer JHF, Chunduri P Tags: Adv Physiol Educ Source Type: research

Patterns of medical student engagement in a second-year pathophysiology course: relationship to USMLE Step 1 performance.
Abstract Historically, attendance has been a marker of academic performance, but the current medical education literature has had mixed results. In addition, attendance is dropping in the preclinical curricula, whereas, at the same time, the focus on United States Medical Licensing Examination Step 1 performance is increasing. This present study is a mixed-method approach correlating student attendance and access to the formal curriculum in a second-year pathophysiology course to performance on Step 1. Additionally, survey and focus group data evaluated the usage and importance of both the formal curriculum and th...
Source: Adv Physiol Educ - September 26, 2019 Category: Universities & Medical Training Authors: Kauffman CA, Derazin M, Asmar A, Kibble JD Tags: Adv Physiol Educ Source Type: research

A virtual experiment improved students' understanding of physiological experimental processes ahead of a live inquiry-based practical class.
Abstract Physiology is commonly taught through direct experience and observation of scientific phenomena in "hands-on" practical laboratory classes. The value of such classes is limited by students' lack of understanding of the underlying theoretical concepts and their lack of confidence with the experimental techniques. In our experience, students follow experimental steps as if following a recipe, without giving thought to the underlying theory and the relationship between the experimental procedure and the research hypotheses. To address this issue, and to enhance student learning, we developed an onl...
Source: Adv Physiol Educ - September 26, 2019 Category: Universities & Medical Training Authors: Quiroga MDM, Choate JK Tags: Adv Physiol Educ Source Type: research

Planning, implementation, and evaluation of multicomponent, case-based learning for first-year Indian medical undergraduates.
In conclusion, MC-CBL appeared to be an effective supplement for the lectures, providing an opportunity for the students to relate the knowledge learned during lectures. PMID: 31553644 [PubMed - in process] (Source: Adv Physiol Educ)
Source: Adv Physiol Educ - September 26, 2019 Category: Universities & Medical Training Authors: Muthukrishnan SP, Chandran DS, Afreen N, Bir M, Dastidar SG, Jayappa H, Mattoo B, Navneet A, Poorasamy J, Roy A, Sharma A, Ghosh D, Deepak KK Tags: Adv Physiol Educ Source Type: research

Computer-aided drug repurposing for cancer therapy: approaches and opportunities to challenge anticancer targets
Publication date: Available online 25 September 2019Source: Seminars in Cancer BiologyAuthor(s): Carla Mottini, Francesco Napolitano, Zhongxiao Li, Xin Gao, Luca CardoneABSTRACTDespite huge efforts made in academic and pharmaceutical worldwide research, current anticancer therapies achieve effective treatment in a limited number of neoplasia cases only. Oncology terms such as big killers - to identify tumours with yet a high mortality rate - or undruggable cancer targets, and chemoresistance, represent the current therapeutic debacle of cancer treatments. In addition, metastases, tumour microenvironments, tumour heterogene...
Source: Seminars in Cancer Biology - September 26, 2019 Category: Cancer & Oncology Source Type: research

Cognitive self-regulation influences pain-related physiology
In this study, participants (N = 41) deployed a cognitive strategy based on reappraisal and imagination to regulate pain up or down on different trials while skin conductance responses (SCRs) and electrocardiogram activity were recorded. Using a machine learning approach, we first developed stimulus-locked SCR and electrocardiogram physiological markers predictive of pain ratings. The physiological markers demonstrated high sensitivity and moderate specificity in predicting pain across 2 data sets, including an independent test data set (N = 84). When we tested the markers on the cognitive self-regulation data, we found th...
Source: Pain - September 26, 2019 Category: Anesthesiology Tags: Research Paper Source Type: research

Machine-learned analysis of the association of next-generation sequencing–based genotypes with persistent pain after breast cancer surgery
Cancer and its surgical treatment are among the most important triggering events for persistent pain, but additional factors need to be present for the clinical manifestation, such as variants in pain-relevant genes. In a cohort of 140 women undergoing breast cancer surgery, assigned based on a 3-year follow-up to either a persistent or nonpersistent pain phenotype, next-generation sequencing was performed for 77 genes selected for known functional involvement in persistent pain. Applying machine-learning and item categorization techniques, 21 variants in 13 different genes were found to be relevant to the assignment of a ...
Source: Pain - September 26, 2019 Category: Anesthesiology Tags: Research Paper Source Type: research

Versatile neuromorphic electronics by modulating synaptic decay of single organic synaptic transistor: From artificial neural networks to neuro-prosthetics
Publication date: November 2019Source: Nano Energy, Volume 65Author(s): Dae-Gyo Seo, Yeongjun Lee, Gyeong-Tak Go, Mingyuan Pei, Sungwoo Jung, Yo Han Jeong, Wanhee Lee, Hea-Lim Park, Sang-Woo Kim, Hoichang Yang, Changduk Yang, Tae-Woo LeeAbstractOrganic neuromorphic electronics are inspired by a biological nervous system. Bio-inspired computing mimics learning and memory in a brain (i.e., the central nervous system), and bio-inspired soft robotics and nervous prosthetics mimics the neural signal transmission of afferent/efferent nerves (i.e., the peripheral nervous system). Synaptic decay time of nerves differ among biologi...
Source: Nano Energy - September 26, 2019 Category: Nanotechnology Source Type: research

Using behaviour change theory to inform an innovative recruitment strategy in a mental health research setting
Publication date: Available online 25 September 2019Source: Journal of Psychiatric ResearchAuthor(s): Michael Musker, Camille Short, Julio Licinio, Ma-Li Wong, Niranjan BidargaddiAbstractRecruitment in mental health research is challenging, as some disorders such as depression or schizophrenia may involve vulnerable participants that lack motivation as part of their illness. A mental health diagnosis can be stigmatising, so privacy and access to hospital-based patient cohorts is carefully controlled. Our team describe a pragmatic portal recruitment process for facilitating timely recruitment into multiple research studies ...
Source: Journal of Psychiatric Research - September 26, 2019 Category: Psychiatry Source Type: research

The promise of neurobiological research in anorexia nervosa
This article reviews new research in the context of existing literature to identify approaches that will advance understanding of the persistence of anorexia nervosa. Recent findings Neuroscience research in anorexia nervosa has yielded disparate findings: no definitive neural mechanism underlying illness vulnerability or persistence has been identified and no clear neural target for intervention has emerged. Recent advances using structural and functional neuroimaging research, as well as new techniques for applying and combining these approaches, have led to a refined understanding of changes in neural architecture am...
Source: Current Opinion in Psychiatry - September 26, 2019 Category: Psychiatry Tags: EATING DISORDERS: Edited by Hans W. Hoek and Anna Keski-Rahkonen Source Type: research

The Capacity for Acute Exercise to Modulate Emotional Memories: A Review of Findings and Mechanisms
Publication date: Available online 25 September 2019Source: Neuroscience & Biobehavioral ReviewsAuthor(s): Dharani Keyan, Richard A. BryantAbstractAnxiety disorders, such as posttraumatic stress disorder, are underpinned by fear learning mechanisms. This review outlines how acute bouts of exercise can moderate fear memory acquisition, consolidation, and extinction. These fear memory mechanisms are central to the development and treatment of anxiety disorders. We propose that the documented effects of acute exercise directly impact key neurobiological processes implicated in fear memory modulation. Central to the relati...
Source: Neuroscience and Biobehavioral Reviews - September 26, 2019 Category: Neuroscience Source Type: research

Engineering a Less Artificial Intelligence
Publication date: 25 September 2019Source: Neuron, Volume 103, Issue 6Author(s): Fabian H. Sinz, Xaq Pitkow, Jacob Reimer, Matthias Bethge, Andreas S. ToliasDespite enormous progress in machine learning, artificial neural networks still lag behind brains in their ability to generalize to new situations. Given identical training data, differences in generalization are caused by many defining features of a learning algorithm, such as network architecture and learning rule. Their joint effect, called “inductive bias,” determines how well any learning algorithm—or brain—generalizes: robust generalizatio...
Source: Neuron - September 26, 2019 Category: Neuroscience Source Type: research

Modal Regression based Greedy Algorithm for Robust Sparse Signal Recovery, Clustering and Classification
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Yulong Wang, Yuan Yan Tang, Cuiming Zou, Luoqing Li, Hong ChenAbstractGreedy algorithm (GA) is an efficient sparse representation framework with numerous applications in machine learning and computer vision. However, conventional GA methods may fail when applied to grossly corrupted data because they iteratively estimate the sparse signal using least squares regression, which is sensitive to gross corruption and outliers. In this paper, we propose a modal regression based greedy algorithm referred as MROMP (modal regression based orthogona...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

MSN: Modality Separation Networks for RGB-D Scene Recognition
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Zhitong Xiong, Yuan Yuan, Qi WangAbstractRGB-D image based indoor scene recognition is a challenging task due to the complex scene layouts and cluttered objects. Although the depth modality can provide extra geometric information, how to better learn the multi-modal features is still an open problem. Considering this, in this paper we propose the modality separation networks to extract the modal-consistent and modal-specific features simultaneously. The motivations of this work are from two aspects: 1) The first one is to learn what is uni...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Dual Triplet Network for Image Zero-Shot Learning
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Zhong Ji, Hai Wang, Yanwei Pang, Ling ShaoAbstractAs a cross-modal task, zero-shot learning (ZSL) is generally achieved by aligning the semantic relationships between different modalities. It is a key issue in the alignment to accurately measure the multi-modal data distances. Although metric learning has been employed in many image ZSL approaches, few of them make full use of the data information. To address this issue, we propose a novel deep metric learning framework called Dual-Triplet Network (DTNet) for image ZSL. The DTNet first pro...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Unsupervised Selective Rank Fusion for Image Retrieval Tasks
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Lucas Pascotti Valem, Daniel Carlos Guimarães PedronetteAbstractSeveral visual features have been developed for content-based image retrieval in last decades, including global, local and deep learning based approaches. However, despite the huge advances on features development and mid-level representations, a single visual descriptor is often insufficient to achieve effective retrieval results in several scenarios. Mainly due to the diverse aspects involved in human visual perception, the combination of different features has been e...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Hybrid Neural Recommendation with Joint Deep Representation Learning of Ratings and Reviews
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Hongtao Liu, Yian Wang, Qiyao Peng, Fangzhao Wu, Lin Gan, Lin Pan, Pengfei JiaoAbstractRating-based methods (e.g., collaborative filtering) in recommendation can explicitly model users and items from their rating patterns, nevertheless suffer from the natural data sparsity problem. In other hand, user-generated reviews can provide rich semantic information of user preference and item features, and can alleviate the sparsity problems of rating data. In fact, ratings and reviews are complementary and can be viewed as two different sides of u...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Video Salient Object Detection via Spatiotemporal Attention Neural Networks
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Yi Tang, Wenbin Zou, Yang Hua, Zhi Jin, Xia LiAbstractRecently, deep convolutional neural networks have been widely introduced into image salient object detection and achieve good performance in this community. However, as the complexity of video scenes, video salient object detection with deep learning models is still a challenge. The specific difficulties come from two aspects. First of all, the deep networks on image saliency detection cannot capture robust motion cues in video sequences. Secondly, as for the spatiotemporal fusing featu...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Data pixelization for predicting completion time of events
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Imam Mustafa Kamal, Hyerim Bae, Nur Ichsan Utama, Choi YulimAbstractNowadays, a company uses many sensors to record its entire activity process; the recorded data are called event-log. However, event-log prevalently contains discrete data that many powerful machine-learning algorithms are unable to deal with. One-hot encoding is an outstanding method for transforming discrete data into a binary vector. Nonetheless, if there are many distinct values, the problem of dimensionality will be incurred. To tackle this issue, we propose a new appr...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Deep Attention User-based Collaborative Filtering for Recommendation
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Jie Chen, Xianshuang Wang, Shu Zhao, Fulan Qian, Yanping ZhangAbstractThe user-based collaborative filtering (UCF) model has been widely used in industry for recommender systems. UCF predicts a user’s interest in an item based on rating information from similar user profiles. A neural network UCF model can learn effectively the high-order relations between users and items, but it cannot distinguish the importance of users in learning process. To mine the complex relationships between users and items, we incorporate a Deep+Shadow patt...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Negation and Speculation Scope Detection Using Recursive Neural Conditional Random Fields
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Hao Fei, Yafeng Ren, Donghong JiAbstractNegation and speculation scope detection is an important task in natural language processing. Previous studies all show that syntactic information is crucial to the task. However, these work mainly focuses on human-designed discrete features and local features extracted from dependency tree, limiting the performance of the task. In this paper, we propose a recursive neural network sequence labeling model, representing whole dependency tree globally and learning automatically syntactic features, for t...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Extreme Semi-supervised Learning for Multiclass Classification
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Chuangquan Chen, Yanfen Gan, Chi-Man VongAbstractSemi-Supervised Support Vector Machines (S3VMs) provide a powerful framework for Semi-Supervised Learning (SSL) tasks which leverage widely available unlabeled data to improve performance. However, there exists three issues in S3VMs: i) S3VMs require concurrently training c one-against-all (OAA) classifiers (c is the number of classes) for multiclass classification, which is prohibitive for large c; ii) S3VMs require huge computational time and large storage (because of large kernel matrix) ...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

BreakHis based Breast Cancer Automatic Diagnosis using Deep Learning: Taxonomy, Survey and Insights
Publication date: Available online 25 September 2019Source: NeurocomputingAuthor(s): Yassir Benhammou, Boujemâa Achchab, Francisco Herrera, Siham TabikAbstractThere are several breast cancer datasets for building Computer Aided Diagnosis systems (CADs) using either deep learning or traditional models. However, most of these datasets impose various trade-offs on practitioners related to their availability or inner clinical value. Recently, a public dataset called BreakHis has been released to overcome these limitations. BreakHis is organized into four magnification levels, each image is labeled according to its main c...
Source: Neurocomputing - September 26, 2019 Category: Neuroscience Source Type: research

Fostering resiliency in families and caregivers of individuals with disabilities
Families with individuals who have a disability are at greater risk of developing psychological problems. However, if these families learn how to cope well, it can increase the strength of the family. The post Fostering resiliency in families and caregivers of individuals with disabilities appeared first on Counseling Today. (Source: Counseling Today)
Source: Counseling Today - September 26, 2019 Category: Psychiatry & Psychology Authors: By Mariagrazia Buttitta Tags: Counseling Today Online Exclusives Rehabilitation & Disability Source Type: research

Teacher fidelity to Conscious Discipline and children’s executive function skills
Publication date: 2nd Quarter 2020Source: Early Childhood Research Quarterly, Volume 51Author(s): Kirsten L. Anderson, Madison Weimer, Mary Wagner FuhsAbstractConscious Discipline is a social-emotional learning classroom management program that uses classroom activities and routines to teach children problem-solving skills and to foster a sense of safety in the classroom. According to the publishers of Conscious Discipline, the program is currently practiced in 47 countries and is widely implemented across the United States, including approximately 11,000 Head Start classrooms and 935 school districts (Loving Guidance Inc....
Source: Early Childhood Research Quarterly - September 26, 2019 Category: Child Development Source Type: research

Maternal support for infant learning: Findings from a randomized controlled trial of doula home visiting services for young mothers
In this study, 312 young, low income mothers from diverse racial/ethnic backgrounds and from four geographic locations were interviewed during pregnancy and then randomized to receive either doula home visiting services or low intensity case management services. At 3 weeks, 3 months, and 13 months postpartum, mothers were again interviewed and were video-recorded while interacting with their infants. Results showed that mothers assigned to the intervention were more likely to read to their infants and engage them in activities that foster cognitive development during early infancy. Additionally, moderation analyses reveale...
Source: Early Childhood Research Quarterly - September 26, 2019 Category: Child Development Source Type: research

Computerized social-emotional assessment measures for early childhood settings
Discussion centers on advantages of using these computerized measures, and how teachers could be supported to use them. (Source: Early Childhood Research Quarterly)
Source: Early Childhood Research Quarterly - September 26, 2019 Category: Child Development Source Type: research

Consumer acceptance of blending plant-based ingredients into traditional meat-based foods: Evidence from the meat-mushroom blend
The objectives of this study are to examine the nature of consumer response to blending plant-based ingredients (mushrooms) into traditional meat-based foods and to understand the individual lifestyle and motivational differences that influence this response. Data is obtained through an online consumer survey and descriptive and structural equation analyses are employed. Results find that consumer acceptance is influenced greatly by their assessment of plant-based foods’ taste, health, sustainability, cost, and novelty. Results also find that assessment is influenced by individual differences in food values and lifes...
Source: Food Quality and Preference - September 26, 2019 Category: Food Science Source Type: research

Multi-criterion mammographic risk analysis supported with multi-label fuzzy-rough feature selection
ConclusionsThe novel approach for mammographic risk analysis based on multiple criteria helps improve classification accuracy using selected informative features, without suffering from the redundancy caused by such complex criteria, with the implemented system demonstrating practical efficacy. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 26, 2019 Category: Bioinformatics Source Type: research

Resilience in rare disease networks.
Authors: Jessop E Abstract A resilient system is one which continues to perform its function or goal during a period of change. The original concept was formed around return to the status quo after major external shocks. Recently the concept of "everyday resilience" has been proposed. Everyday resilience is the adaptive and learning response of systems to the daily disturbance of normal routines. For everyday resilience, human factors are as important as physical resources. Rare disease networks can use several strategies to build resilience. PMID: 31553325 [PubMed - in process] (Source: Annali dell I...
Source: Annali dell Istituto Superiore di Sanita - September 26, 2019 Category: General Medicine Tags: Ann Ist Super Sanita Source Type: research

Understanding the Broker Role of Clinician–Scientists: A Realist Review on How They Link Research and Practice
Conclusions The mechanisms found may provide insight for interventions aiming to support clinician–scientists in their broker role. The authors expect that if more attention is paid to learning multidimensional skills and management support for the broker role is strengthened, stronger links between research and practice could be forged. (Source: Academic Medicine)
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Reviews Source Type: research

An Introduction to Machine Learning for Clinicians
The technology at the heart of the most innovative progress in health care artificial intelligence (AI) is in a subdomain called machine learning (ML), which describes the use of software algorithms to identify patterns in very large datasets. ML has driven much of the progress of health care AI over the past 5 years, demonstrating impressive results in clinical decision support, patient monitoring and coaching, surgical assistance, patient care, and systems management. Clinicians in the near future will find themselves working with information networks on a scale well beyond the capacity of human beings to grasp, thereby ...
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Perspectives Source Type: research

Health Systems Science: The “Broccoli” of Undergraduate Medical Education
Health system leaders are calling for reform of medical education programs to meet evolving needs of health systems. U.S. medical schools have initiated innovative curricula related to health systems science (HSS), which includes competencies in value-based care, population health, system improvement, interprofessional collaboration, and systems thinking. Successful implementation of HSS curricula is challenging because of the necessity for new curricular methods, assessments, and educators and for resource allocation. Perhaps most notable of these challenges, however, is students’ mixed receptivity. Although many st...
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Perspectives Source Type: research

Treating the “Not-Invented-Here Syndrome” in Medical Leadership: Learning From the Insights of Outside Disciplines
Physicians are being increasingly called upon to engage in leadership at all levels of modern health organizations, leading many to call for greater research and training interventions regarding physician leadership development. Yet, within these calls to action, the authors note a troubling trend toward siloed, medicine-specific approaches to leadership development and a broad failure to learn from the evidence and insight of other relevant disciplines, such as the organizational sciences. The authors describe how this trend reflects what has been called the “not-invented-here syndrome” (NIHS)—a commonly...
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Invited Commentaries Source Type: research

Building Provider–Caregiver Partnerships: Curricula for Medical Students and Residents
Problem A disconnect exists between caregivers and health care providers, resulting in fragmented communication, which increases caregiver stress and compromises patient care. Although providers have a responsibility to recognize caregiver burden, they receive scant training on issues important to caregivers. Approach From 2014 to 2017, as part of the Building Caregiver Partnerships Through Interprofessional Education project—a collaborative effort between Northeast Ohio Medical University and Summa Health—the authors developed curricula to foster effective partnerships between health care providers and ca...
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Innovation Reports Source Type: research

My First Terrible Diagnosis
No abstract available (Source: Academic Medicine)
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Teaching and Learning Moments Source Type: research

Reflections on a New Curriculum
No abstract available (Source: Academic Medicine)
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Teaching and Learning Moments Source Type: research

Integrating Robotic Technology Into Resident Training: Challenges and Recommendations From the Front Lines
Conclusions Surgical educators should consider technique versus tool, timing of exposure to the tool, overlapping and varying features of robotic and laparoscopic surgery, and use of the dual console as they develop curricula to ensure thorough acquisition and synthesis of all elements of robotic surgery. (Source: Academic Medicine)
Source: Academic Medicine - September 26, 2019 Category: Universities & Medical Training Tags: Research Reports Source Type: research