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Problem-based learning

Eli Gibson, Wenqi Li, Carole Sudre, Lucas Fidon, Dzhoshkun I Shakir, Guotai Wang, Zach Eaton-Rosen, Robert Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Marc Modat, Dean C Barratt, Sébastien Ourselin, M Jorge Cardoso, Tom Vercauteren
BACKGROUND AND OBJECTIVES: Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups...
May 2018: Computer Methods and Programs in Biomedicine
Tzu-I Tsai, Shoou-Yih D Lee, Wen-Ry Yu
We evaluated the effectiveness of a problem-based learning (PBL) health literacy program aimed to improve health literacy, health empowerment, navigation efficacy, and health care utilization among immigrant women in Taiwan. We employed a quasi-experimental design that included surveys at the baseline, immediately after the intervention, and 6 months after the intervention. The intervention group participated in a 10-session PBL health literacy program and the comparison group did not. Results showed that 6 months after the intervention, the intervention group had significantly fewer ER visits and hospitalizations than the comparison group...
March 15, 2018: Journal of Health Communication
Wei Wang, Yan Yan, Feiping Nie, Shuicheng Yan, Nicu Sebe
Graph-based dimensionality reduction techniques have been widely and successfully applied to clustering and classification tasks. The basis of these algorithms is the constructed graph which dictates their performance. In general, the graph is defined by the input affinity matrix. However, the affinity matrix derived from the data is sometimes suboptimal for dimension reduction as the data used are very noisy. To address this issue, we propose the projective unsupervised flexible embedding models with optimal graph (PUFE-OG)...
June 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Sarah Ackerman
The ethical underpinnings of writing about patients are explored, the question of how best to undertake the writing of case reports being subordinated to a more general question about the ethics of choosing how or whether to write. An unsolvable paradox is encountered here: that we need to write or speak about our clinical work in order to conceptualize and understand the work we are doing, but that in the very gesture of doing so, we are breaking a fundamental bond with the patient. This conundrum is viewed from a number of vantage points...
February 2018: Journal of the American Psychoanalytic Association
Alexander Skulmowski, Günter Daniel Rey
Research on learning and education is increasingly influenced by theories of embodied cognition. Several embodiment-based interventions have been empirically investigated, including gesturing, interactive digital media, and bodily activity in general. This review aims to present the most important theoretical foundations of embodied cognition and their application to educational research. Furthermore, we critically review recent research concerning the effectiveness of embodiment interventions and develop a taxonomy to more properly characterize research on embodied cognition...
2018: Cognitive Research: Principles and Implications
Akhilesh S Pathipati, Christine K Cassel
Although they enter school with enthusiasm for a career in medicine, medical students in the United States subsequently report high levels of burnout and disillusionment. As medical school leaders consider how to address this problem, they can look to business schools as one source of inspiration. In this Commentary, the authors argue-based on their collective experience in both medical and business education-that medical schools can draw three lessons from business schools that can help reinvigorate students...
March 13, 2018: Academic Medicine: Journal of the Association of American Medical Colleges
Keisuke Takahashi
Prediction of the magnetic moment of binary body centered cubic (BCC) is explored in terms of first principle calculations and data science. A dataset of 1,541 binary BCC materials constructed by first principle calculations is implemented for data mining. Descriptors for determining the magnetic moment are explored using machine learning, where classification and regression models are both implemented. Data mining reveals that two descriptors are responsible for classifying whether the materials have zero or nonzero magnetic moments and can also classify which groups of magnetic moments they belong to ($\mu_{B}$ $<$ 1, 1 $\leq$ $\mu_{B}$ $<$2,or 2 $\leq$ $\mu_{B}$ $<$ 3) where the average scores produced in cross validation indicate 80$\%$ and 91$\%$ accuracy, respectively...
March 14, 2018: Chemphyschem: a European Journal of Chemical Physics and Physical Chemistry
Veronica Restelli, Annemarie Taylor, Douglas Cochrane, Michael A Noble
BACKGROUND: This article reports on the findings of 12,278 laboratory related safety events that were reported through the British Columbia Patient Safety & Learning System Incident Reporting System. METHODS: The reports were collected from 75 hospital-based laboratories over a 33-month period and represent approximately 4.9% of all incidents reported. RESULTS: Consistent with previous studies 76% of reported incidents occurred during the pre-analytic phase of the laboratory cycle, with twice as many associated with collection problems as with clerical problems...
June 27, 2017: Diagnosis
Xiajing Gong, Meng Hu, Liang Zhao
Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data...
March 13, 2018: Clinical and Translational Science
Dolly A Parasrampuria, Leslie Z Benet, Amarnath Sharma
New drug development is both resource and time intensive, where later clinical stages result in significant costs. We analyze recent late-stage failures to identify drugs where failures result from inadequate scientific advances as well as drugs where we believe pitfalls could have been avoided. These can be broadly classified into two categories: 1) where science is mature and the failures can be avoided through rigorous and prospectively determined decision-making criteria, scientific curiosity, and discipline to follow up on emerging findings; and 2) where problems encountered in Phase 3 failures cannot be explained at this time, as the science is not sufficiently advanced and companies/investigators need to recognize the possibility of deficiency of our knowledge...
March 13, 2018: AAPS Journal
Mantas Mikaitis, Garibaldi Pineda García, James C Knight, Steve B Furber
SpiNNaker is a digital neuromorphic architecture, designed specifically for the low power simulation of large-scale spiking neural networks at speeds close to biological real-time. Unlike other neuromorphic systems, SpiNNaker allows users to develop their own neuron and synapse models as well as specify arbitrary connectivity. As a result SpiNNaker has proved to be a powerful tool for studying different neuron models as well as synaptic plasticity-believed to be one of the main mechanisms behind learning and memory in the brain...
2018: Frontiers in Neuroscience
Ping Zhang, Lihong Xu
Complicated image scene of the agricultural greenhouse plant images makes it very difficult to obtain precise manual labeling, leading to the hardship of getting the accurate training set of the conditional random field (CRF). Considering this problem, this paper proposed an unsupervised conditional random field image segmentation algorithm ULCRF (Unsupervised Learning Conditional Random Field), which can perform fast unsupervised segmentation of greenhouse plant images, and further the plant organs in the image, i...
March 13, 2018: Scientific Reports
Giada Acciaroli, Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino
Minimally invasive continuous glucose monitoring (CGM) sensors are wearable medical devices that provide real-time measurement of subcutaneous glucose concentration. This can be of great help in the daily management of diabetes. Most of the commercially available CGM devices have a wire-based sensor, usually placed in the subcutaneous tissue, which measures a "raw" current signal via a glucose-oxidase electrochemical reaction. This electrical signal needs to be translated in real-time to glucose concentration through a calibration process...
March 13, 2018: Biosensors
Kyungja Kang, Mi Yu
BACKGROUND: Student self-debriefing promotes self-confidence, helps to increase clinical performance, and is a more cost-effective method than is traditional instructor-led debriefing in simulation-based learning. OBJECTIVES: This study compared the effectiveness of debriefing-in terms of the problem-solving process, team effectiveness, debriefing assessment, and debriefing satisfaction-between an experimental group who received both student self-debriefing (SSD) and instructor debriefing (ID) and a control group who received only instructor debriefing...
March 2, 2018: Nurse Education Today
Courtney Rogers, Joy Johnson, Brianne Nueslein, David Edmunds, Rupa S Valdez
As chronic conditions are on the rise in the USA, management initiatives outside of the inpatient setting should be explored to reduce associated cost and access disparities. Chronic conditions disproportionately affect African American public housing residents due to the effects of historical marginalization on the manifestation of economic and social problems exacerbating health disparities and outcomes. Informed by participatory research action tenets, this study focused on identifying the challenges to management of chronic conditions and developing community-envisioned initiatives to address these challenges in a predominantly African American public housing community...
March 12, 2018: Journal of Racial and Ethnic Health Disparities
Venkataramana Kandi, Parimala Reddy Basireddy
Introduction Medical education involves training necessary to become a physician or a surgeon. This includes various levels of training like undergraduate, internship, and postgraduate training. Medical education can be quite complex, since it involves training in pre-clinical subjects (anatomy, physiology, biochemistry), the para-clinical subjects (microbiology, pathology, pharmacology, and forensic medicine), and a discrete group of clinical subjects that include general medicine, surgery, obstetrics and gynaecology, ear, nose and throat specialization, paediatrics, cardiology, pulmonology, dermatology, ophthalmology, and orthopaedics, and many other clinical specializations and super specialities (cardio-thoracic surgery, neurosurgery, etc...
January 5, 2018: Curēus
Xiao He, Lukas Folkman, Karsten Borgwardt
Motivation: Large-scale screenings of cancer cell lines with detailed molecular profiles against libraries of pharmacological compounds are currently being performed in order to gain a better understanding of the genetic component of drug response and to enhance our ability to recommend therapies given a patient's molecular profile. These comprehensive screens differ from the clinical setting in which (1) medical records only contain the response of a patient to very few drugs, (2) drugs are recommended by doctors based on their expert judgment, and (3) selecting the most promising therapy is often more important than accurately predicting the sensitivity to all potential drugs...
March 8, 2018: Bioinformatics
Viktor Riklefs, Gulmira Abakassova, Aliya Bukeyeva, Sholpan Kaliyeva, Bakhtiyar Serik, Alma Muratova, Raushan Dosmagambetova
BACKGROUND: Medical education in Kazakhstan has been literally transformed in the past 10 years. Kazakhstan inherited the Soviet-time discipline-based teacher-centered system of education when no decisions could be made independently. The curriculum was mostly governed in a traditional way, with lectures being the core, little use of e-learning tools, and assessment through oral exams and multiple-choice questions. Most of the universities still preserve the subject-based curriculum with elements of integrated learning...
March 11, 2018: Medical Teacher
Fuqiang Qiao, Fenfen Sun, Fengying Li, Xiaoli Ling, Li Zheng, Lin Li, Xiuyan Guo, Zoltan Dienes
Fluency influences grammaticality judgments of visually presented strings in artificial grammar learning (AGL). Of many potential sources that engender fluency, symmetry is considered to be an important factor. However, symmetry may function differently for visual and auditory stimuli, which present computationally different problems. Thus, the current study aimed to examine whether objectively manipulating fluency by speeding up perception (i.e., manipulating the inter-stimulus interval, ISI, between each syllable of a string) influenced judgments of tonal strings; and thus how symmetry-based fluency might influence judgments...
2018: Frontiers in Psychology
Xiaokang Yu, Na Lei, Yalin Wang, Xianfeng Gu
3D dynamic surface tracking is an important research problem and plays a vital role in many computer vision and medical imaging applications. However, it is still challenging to efficiently register surface sequences which has large deformations and strong noise. In this paper, we propose a novel automatic method for non-rigid 3D dynamic surface tracking with surface Ricci flow and Teichmüller map methods. According to quasi-conformal Teichmüller theory, the Techmüller map minimizes the maximal dilation so that our method is able to automatically register surfaces with large deformations...
October 2017: Proceedings
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