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Retrieval-based learning

Marieke J van Gelderen, Mirjam J Nijdam, Eric Vermetten
Despite an array of evidence-based psychological treatments for patients with a posttraumatic stress disorder (PTSD), a majority of patients do not fully benefit from the potential of these therapies. In veterans with PTSD, up to two-thirds retain their diagnosis after psychotherapy and often their disorder is treatment-resistant, which calls for improvement of therapeutic approaches for this population. One of the factors hypothesized to underlie low response in PTSD treatment is high behavioral and cognitive avoidance to traumatic reminders...
2018: Frontiers in Psychiatry
Nathan Foulquier, Pascal Redou, Christophe Le Gal, Bénédicte Rouvière, Jacques-Olivier Pers, Alain Saraux
Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of systemic autoimmune diseases (SADs) over the last decade...
May 17, 2018: Human Vaccines & Immunotherapeutics
Sandra Turner, Ming-Ka Chan, Judy McKimm, Graham Dickson, Timothy Shaw
Purpose Doctors play a central role in leading improvements to healthcare systems. Leadership knowledge and skills are not inherent, however, and need to be learned. General frameworks for medical leadership guide curriculum development in this area. Explicit discipline-linked competency sets and programmes provide context for learning and likely enhance specialty trainees' capability for leadership at all levels. The aim of this review was to summarise the scholarly literature available around medical specialty-specific competency-based curricula for leadership in the post-graduate training space...
May 8, 2018: Leadership in Health Services
Gokhan Bakal, Preetham Talari, Elijah V Kakani, Ramakanth Kavuluru
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying different causal relations between biomedical entities is also critical to understand biomedical processes. Generally, natural language processing (NLP) and machine learning are used to predict specific relations between any given pair of entities using the distant supervision approach...
May 12, 2018: Journal of Biomedical Informatics
Inken Rothkirch, Stephan Wolff, Nils G Margraf, Anya Pedersen, Karsten Witt
Previous studies demonstrated the influence of the post-learning period on procedural motor memory consolidation. In an early period after the acquisition, motor skills are vulnerable to modifications during wakefulness. Indeed, specific interventions such as world-list learning within this early phase of motor memory consolidation seem to enhance motor performance as an indicator for successful consolidation. This finding highlights the idea that manipulations of procedural and declarative memory systems during the early phase of memory consolidation over wakefulness may influence off-line consolidation...
2018: Frontiers in Neuroscience
Yeqing Li, Wei Liu, Junzhou Huang
Recently with the explosive growth of visual content on the Internet, large-scale image search has attracted intensive attention. It has been shown that mapping high-dimensional image descriptors to compact binary codes can lead to considerable efficiency gains in both storage and performing similarity computation of images. However, most existing methods still suffer from expensive training devoted to large-scale binary code learning. To address this issue, we propose a sub-selection based matrix manipulation algorithm, which can significantly reduce the computational cost of code learning...
June 2018: IEEE Transactions on Pattern Analysis and Machine Intelligence
Charlene Williams, Susan Perlis, John Gaughan, Sangita Phadtare
Learner-centered pedagogical methods that are based on clinical application of basic science concepts through active learning and problem solving are shown to be effective for improving knowledge retention. As the clinical relevance of biochemistry is not always apparent to health-profession students, effective teaching of medical biochemistry should highlight the implications of biochemical concepts in pathology, minimize memorization, and make the concepts memorable for long-term retention. Here, we report the creation and successful implementation of a flipped jigsaw activity that was developed to stimulate interest in learning biochemistry among medical students...
May 6, 2018: Biochemistry and Molecular Biology Education
Mitsuko Onda, Nobumasa Takagaki
 Osaka University of Pharmaceutical Sciences has included an evidence-based medicine (EBM) exercise in the introductory education for clinical practice for 4th-year pharmacy students since 2015. The purpose of this exercise is to learn the process of practice and basic concepts of EBM, especially to cultivate the practical ability to solve patients' problems and answer their questions. Additionally, in 2016, we have attempted flipped teaching. The students are instructed to review the basic knowledge necessary for active learning in this exercise by watching video teaching materials and to bring reports summarizing the contents on the flipped teaching days...
2018: Yakugaku Zasshi: Journal of the Pharmaceutical Society of Japan
Ryuichi Ogawa
 Training pharmacy students to become future clinical pharmacists is an important mission in the 6-year school of pharmacy curriculum in Japan. Since 2014, we have conducted an on-campus practical training program to develop basic skills in clinical pharmacy for third-year pharmacy students at Meiji Pharmaceutical University. This training program includes searching for and retrieving drug information; interpretation of laboratory findings, vital signs, and physical examinations; literature appraisal; and professional writing...
2018: Yakugaku Zasshi: Journal of the Pharmaceutical Society of Japan
Guy Tsafnat, Paul Glasziou, George Karystianis, Enrico Coiera
BACKGROUND: Screening candidate studies for inclusion in a systematic review is time-consuming when conducted manually. Automation tools could reduce the human effort devoted to screening. Existing methods use supervised machine learning which train classifiers to identify relevant words in the abstracts of candidate articles that have previously been labelled by a human reviewer for inclusion or exclusion. Such classifiers typically reduce the number of abstracts requiring manual screening by about 50%...
April 25, 2018: Systematic Reviews
Oscar García-Olalla, Enrique Alegre, Laura Fernández-Robles, Eduardo Fidalgo, Surajit Saikia
Textile based image retrieval for indoor environments can be used to retrieve images that contain the same textile, which may indicate that scenes are related. This makes up a useful approach for law enforcement agencies who want to find evidence based on matching between textiles. In this paper, we propose a novel pipeline that allows searching and retrieving textiles that appear in pictures of real scenes. Our approach is based on first obtaining regions containing textiles by using MSER on high pass filtered images of the RGB, HSV and Hue channels of the original photo...
April 25, 2018: Sensors
Alejandro Baldominos, Yago Saez, Pedro Isasi
Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset...
April 23, 2018: Sensors
Payam Karisani, Zhaohui S Qin, Eugene Agichtein
January 1, 2018: Database: the Journal of Biological Databases and Curation
Brett Sadowski, Sarah Cantrell, Adam Barelski, Patrick G O'Malley, Joshua D Hartzell
Background : Leadership is a critical component of physician competence, yet the best approaches for developing leadership skills for physicians in training remain undefined. Objective : We systematically reviewed the literature on existing leadership curricula in graduate medical education (GME) to inform leadership program development. Methods : Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we searched MEDLINE, ERIC, EMBASE, and MedEdPORTAL through October 2015 using search terms to capture GME leadership curricula...
April 2018: Journal of Graduate Medical Education
Guoyu Tang, Yuan Ni, Keqiang Wang, Qin Yong
The online patient question and answering (Q&A) system attracts an increasing amount of users in China. Patient will post their questions and wait for doctors' response. To avoid the lag time involved with the waiting and to reduce the workload on the doctors, a better method is to automatically retrieve the semantically equivalent question from the archive. We present a Generative Adversarial Networks (GAN) based approach to automatically retrieve patient question. We apply supervised deep learning based approaches to determine the similarity between patient questions...
2018: Studies in Health Technology and Informatics
Guoxian Dai, Jin Xie, Yi Fang
How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape...
July 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Sourabh Chachan, Hamid Ramatullah Bin Abd Razak, Wee Lim Loo, John Carson Allen, Dinesh Shree Kumar
PURPOSE: Despite proven biomechanical superiority and resultant superior clinical outcomes, pedicle instrumentation in cervical spine is not widely practiced due to technical difficulties, steep learning curve, and possible potential catastrophic complications due to screw misplacement. This study was undertaken with the purpose to evaluate the feasibility, accuracy, and complications of cervical pedicle screw instrumentation solely using O-arm-based 3D navigation technology. METHODS: Prospectively maintained data from a single-surgeon case series were retrospectively analyzed...
April 12, 2018: European Spine Journal
Yibing Ma, Zhiguo Jiang, Haopeng Zhang, Fengying Xie, Yushan Zheng, Huaqiang Shi, Yu Zhao, Jun Shi
BACKGROUND AND OBJECTIVE: Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels...
June 2018: Computer Methods and Programs in Biomedicine
John Schwoebel, Acasia K Depperman, Jessica L Scott
Spaced retrieval practice results in better long-term retention than massed retrieval practice. The episodic context account of this effect suggests that updated representations of the more distinct temporal contexts associated with spaced retrievals facilitate later recall. We examined whether environmental context, in addition to temporal context, may also play a role in retrieval-based learning. Participants studied and then attempted to retrieve the English translations of Swahili words during four acquisition blocks of trials...
April 12, 2018: Memory
Vanessa M Loaiza, Valérie Camos
Two main mechanisms, articulatory rehearsal and attentional refreshing, are argued to be involved in the maintenance of verbal information in working memory (WM). Whereas converging research has suggested that rehearsal promotes the phonological representations of memoranda in working memory, little is known about the representations that refreshing may promote. Not only would examining this question address this gap in the literature, but the investigation has profound implications for different theoretical proposals of how refreshing functions and on the relationships between WM and long-term memory (LTM)...
April 12, 2018: Journal of Experimental Psychology. Learning, Memory, and Cognition
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