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https://www.readbyqxmd.com/read/28649016/epileptic-seizure-detection-based-on-imbalanced-classification-and-wavelet-packet-transform
#1
Qi Yuan, Weidong Zhou, Liren Zhang, Fan Zhang, Fangzhou Xu, Yan Leng, Dongmei Wei, Meina Chen
PURPOSE: Automatic seizure detection is significant for the diagnosis of epilepsy and the reduction of massive workload for reviewing continuous EEG recordings. METHODS: Compared with the long non-seizure periods, the durations of the seizure events are much shorter in the continuous EEG recordings. So the seizure detection task can be regarded as an imbalanced classification problem. In this paper, a novel method based on the weighted extreme learning machine (ELM) is proposed for seizure detection with imbalanced EEG data distribution...
June 8, 2017: Seizure: the Journal of the British Epilepsy Association
https://www.readbyqxmd.com/read/28648219/primary-care-collaboration-to-improve-diagnosis-and-screening-for-colorectal-cancer
#2
Gordon D Schiff, Trudy Bearden, Lindsay Swain Hunt, Jennifer Azzara, Jay Larmon, Russell S Phillips, Sara Singer, Brandon Bennett, Jonathan R Sugarman, Asaf Bitton, Andrew Ellner
BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer death, reducible by screening and early diagnosis, yet many patients fail to receive recommended screening. As part of an academic improvement collaborative, 25 primary care practices worked to improve CRC screening and diagnosis. METHODS: The project featured triannual learning sessions, monthly conference calls, practice coach support, and monthly reporting. The project phases included literature review and interviews with national leaders/organizations, development of driver diagrams to identify key factors and change ideas, project launch and practice team planning, and a practice improvement phase...
July 2017: Joint Commission Journal on Quality and Patient Safety
https://www.readbyqxmd.com/read/28646506/three-lessons-for-genetic-toxicology-from-baseball-analytics
#3
EDITORIAL
Stephen D Dertinger
In many respects the evolution of baseball statistics mirrors advances made in the field of genetic toxicology. From its inception, baseball and statistics have been inextricably linked. Generations of players and fans have used a number of relatively simple measurements to describe team and individual player's current performance, as well as for historical record-keeping purposes. Over the years, baseball analytics has progressed in several important ways. Early advances were based on deriving more meaningful metrics from simpler forerunners...
June 24, 2017: Environmental and Molecular Mutagenesis
https://www.readbyqxmd.com/read/28645319/architectural-frameworks-defining-the-structures-for-implementing-learning-health-systems
#4
Lysanne Lessard, Wojtek Michalowski, Michael Fung-Kee-Fung, Lori Jones, Agnes Grudniewicz
BACKGROUND: The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort...
June 23, 2017: Implementation Science: IS
https://www.readbyqxmd.com/read/28644809/structured-kernel-dictionary-learning-with-correlation-constraint-for-object-recognition
#5
Zhengjue Wang, Yinghua Wang, Hongwei Liu, Hao Zhang
In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes...
June 21, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28644806/discriminative-deep-metric-learning-for-face-and-kinship-verification
#6
Jiwen Lu, Junlin Hu, Yap-Peng Tan
This paper presents a new discriminative deep metric learning (DDML) method for face and kinship verification in wild conditions. While metric learning has achieved reasonably good performance in face and kinship verification, most existing metric learning methods aim to learn a single Mahalanobis distance metric to maximize the inter-class variations and minimize the intra-class variations, which cannot capture the nonlinear manifold where face images usually lie on. To address this, we propose a DDML method to train a deep neural network to learn a set of hierarchical nonlinear transformations to project face pairs into the same latent feature space, under which the distance of each positive pair is reduced and that of each negative pair is enlarged, respectively...
June 20, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28640683/the-public-health-practitioner-of-the-future
#7
Paul Campbell Erwin, Ross C Brownson
The requisite capacities and capabilities of the public health practitioner of the future are being driven by multiple forces of change, including public health agency accreditation, climate change, health in all policies, social media and informatics, demographic transitions, globalized travel, and the repercussions of the Affordable Care Act. We describe five critical capacities and capabilities that public health practitioners can build on to successfully prepare for and respond to these forces of change: systems thinking and systems methods, communication capacities, an entrepreneurial orientation, transformational ethics, and policy analysis and response...
June 22, 2017: American Journal of Public Health
https://www.readbyqxmd.com/read/28640036/a-constructive-reframing-of-student-roles-and-systems-learning-in-medical-education-using-a-communities-of-practice-lens
#8
Jed D Gonzalo, Britta M Thompson, Paul Haidet, Karen Mann, Daniel R Wolpaw
Health systems are in the midst of a transformation that is being driven by a variety of forces. This has important implications for medical educators because clinical practice environments play a key role in learning and professional development, and evolving health systems are beginning to demand that providers have "systems-ready" knowledge, attitudes, and skills. Such implications provide a clear mandate for medical schools to modify their goals and prepare physicians to practice flexibly within teams and effectively contribute to the improvement of health care delivery...
June 20, 2017: Academic Medicine: Journal of the Association of American Medical Colleges
https://www.readbyqxmd.com/read/28639526/using-technology-in-research
#9
Liz Halcombs
[Figure: see text] In the past 25 years, the growth of the internet and associated technology has significantly changed the way in which we communicate, seek information and engage with others across all aspects of our lives ( Meyer et al 2016 ). Academia in particular has been transformed with a growth in online learning and the expanding use of technology in research.
June 22, 2017: Nurse Researcher
https://www.readbyqxmd.com/read/28638516/a-professionalism-curricular-model-to-promote-transformative-learning-among-residents
#10
Cecile M Foshee, Ali Mehdi, S Beth Bierer, Elias I Traboulsi, J Harry Isaacson, Abby Spencer, Cassandra Calabrese, Brian B Burkey
BACKGROUND: Using the frameworks of transformational learning and situated learning theory, we developed a technology-enhanced professionalism curricular model to build a learning community aimed at promoting residents' self-reflection and self-awareness. The RAPR model had 4 components: (1) Recognize: elicit awareness; (2) Appreciate: question assumptions and take multiple perspectives; (3) Practice: try new/changed perspectives; and (4) Reflect: articulate implications of transformed views on future actions...
June 2017: Journal of Graduate Medical Education
https://www.readbyqxmd.com/read/28635623/compressed-sensing-reconstruction-based-on-block-sparse-bayesian-learning-in-bearing-condition-monitoring
#11
Jiedi Sun, Yang Yu, Jiangtao Wen
Remote monitoring of bearing conditions, using wireless sensor network (WSN), is a developing trend in the industrial field. In complicated industrial environments, WSN face three main constraints: low energy, less memory, and low operational capability. Conventional data-compression methods, which concentrate on data compression only, cannot overcome these limitations. Aiming at these problems, this paper proposed a compressed data acquisition and reconstruction scheme based on Compressed Sensing (CS) which is a novel signal-processing technique and applied it for bearing conditions monitoring via WSN...
June 21, 2017: Sensors
https://www.readbyqxmd.com/read/28633205/advancing-the-science-of-myocardial-recovery-with-mechanical-circulatory-support-a-working-group-of-the-national-heart-lung-and-blood-institute
#12
EDITORIAL
Stavros G Drakos, Francis D Pagani, Martha S Lundberg, Timothy J Baldwin
The medical burden of heart failure (HF) has spurred interest in clinicians and scientists to develop therapies to restore the function of a failing heart. To advance this agenda, the National Heart, Lung, and Blood Institute (NHLBI) convened a Working Group of experts from June 2 to 3, 2016, in Bethesda, Maryland, to develop NHLBI recommendations aimed at advancing the science of cardiac recovery in the setting of mechanical circulatory support (MCS). MCS devices effectively reduce volume and pressure overload that drives the cycle of progressive myocardial dysfunction, thereby triggering structural and functional reverse remodeling...
July 2017: Journal of Thoracic and Cardiovascular Surgery
https://www.readbyqxmd.com/read/28628331/quantum-cascade-laser-spectral-histopathology-breast-cancer-diagnostics-using-high-throughput-chemical-imaging
#13
Michael John Pilling, Alex Henderson, Peter Gardner
Fourier Transform Infrared (FT-IR) microscopy, coupled with machine learning approaches, has been demonstrated to be a powerful technique for identifying abnormalities in human tissue. The ability to objectively identify the pre-diseased state, and diagnose cancer with high levels of accuracy, has the potential to revolutionise current histopathological practice. Despite recent technological advances in FT-IR microscopy, sample throughput and speed of acquisition are key barriers to clinical translation. Wide-field quantum cascade laser (QCL) infrared imaging systems with large focal plane array detectors and utilising discrete frequency imaging, have demonstrated that large tissue microarrays (TMA) can be imaged in a matter of minutes...
June 19, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/28620025/growing-functions-of-the-escrt-machinery-in-cell-biology-and-viral-replication
#14
REVIEW
Edward J Scourfield, Juan Martin-Serrano
The vast expansion in recent years of the cellular processes promoted by the endosomal sorting complex required for transport (ESCRT) machinery has reinforced its identity as a modular system that uses multiple adaptors to recruit the core membrane remodelling activity at different intracellular sites and facilitate membrane scission. Functional connections to processes such as the aurora B-dependent abscission checkpoint also highlight the importance of the spatiotemporal regulation of the ESCRT machinery...
June 15, 2017: Biochemical Society Transactions
https://www.readbyqxmd.com/read/28619411/where-we-fall-down-tensions-in-teaching-social-medicine-and-global-health
#15
Amy Finnegan, Michelle Morse, Marisa Nadas, Michael Westerhaus
BACKGROUND: As global health interest has risen, so too has the relevance of education on the social determinants of health and health equity. Social medicine offers a particularly salient framework for educating on the social determinants of health, health disparities, and health equity. SocMed and EqualHealth, 2 unique but related organizations, offer annual global health courses in Uganda, Haiti, and the United States, which train students to understand and respond to the social determinants of health through praxis, self-reflection and self-awareness, and building collaborative partnerships across difference...
March 2017: Annals of Global Health
https://www.readbyqxmd.com/read/28619409/student-reflection-papers-on-a-global-clinical-experience-a-qualitative-study
#16
Carmi Z Margolis, Robert M Rohrbaugh, Luisa Tsang, Jennifer Fleischer, Mark J Graham, Anne Kellett, Janet P Hafler
BACKGROUND: Many of the 70,000 graduating US medical students [per year] have reported participating in a global health activity at some stage of medical school. This case study design provided a method for understanding the student's experience that included student's learning about culture, health disparities, exposure and reaction to a range of diseases actually encountered. The broad diversity of themes among students indicated that the GCE provided a flexible, personalized experience...
March 2017: Annals of Global Health
https://www.readbyqxmd.com/read/28617013/the-role-of-policy-in-supporting-clinician-led-research-on-behavioral-health-integration
#17
Nathaniel Z Counts
In Best Care at Lower Cost, the Institute of Medicine laid out a vision for continuously learning health systems (Institute of Medicine of the National Academies, 2016). This issue of Families, Systems, & Health represents a substantial step toward this vision, with on-the-ground clinicians and administrators testing empirically informed hypotheses about practice transformation and population health management, and using those results to produce shared learning within and across systems. While the studies in this issue demonstrate that producing generalizable knowledge from clinician-led initiatives is feasible, they also demonstrate that the current system does not adequately support clinicians in doing so...
June 2017: Families, Systems & Health: the Journal of Collaborative Family Healthcare
https://www.readbyqxmd.com/read/28613184/online-feature-transformation-learning-for-cross-domain-object-category-recognition
#18
Xuesong Zhang, Yan Zhuang, Wei Wang, Witold Pedrycz
In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation...
June 9, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28613172/learning-the-image-processing-pipeline
#19
Haomiao Jiang, Qiyuan Tian, Joyce Farrell, Brian Wandell
Many creative ideas are being proposed for image sensor designs, and these may be useful in applications ranging from consumer photography to computer vision. To understand and evaluate each new design, we must create a corresponding image processing pipeline that transforms the sensor data into a form that is appropriate for the application. The need to design and optimize these pipelines is time-consuming and costly. We explain a method that combines machine learning and image systems simulation that automates the pipeline design...
June 8, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28613171/simultaneous-feature-and-dictionary-learning-for-image-set-based-face-recognition
#20
Jiwen Lu, Gang Wang, Jie Zhou
In this paper, we propose a simultaneous feature and dictionary learning (SFDL) method for image set based face recognition, where each training and testing example contains a set of face images which were captured from different variations of pose, illumination, expression, resolution and motion. While a variety of feature learning and dictionary learning methods have been proposed in recent years and some of them have been successfully applied to image set based face recognition, most of them learn features and dictionaries for facial image sets individually, which may not be powerful enough because some discriminative information for dictionary learning may be compromised in the feature learning stage if they are applied sequentially, and vice versa...
June 8, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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