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https://www.readbyqxmd.com/read/29792208/automated-chest-screening-based-on-a-hybrid-model-of-transfer-learning-and-convolutional-sparse-denoising-autoencoder
#1
Changmiao Wang, Ahmed Elazab, Fucang Jia, Jianhuang Wu, Qingmao Hu
OBJECTIVE: In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, high accuracy of diagnosis by an automated system can reduce the radiologist's workload on scrutinizing the medical images. METHOD: We present a deep learning model in order to efficiently detect abnormal levels or identify normal levels during mass chest screening so as to obtain the probability confidence of the CXRs...
May 23, 2018: Biomedical Engineering Online
https://www.readbyqxmd.com/read/29791463/recurrent-spatio-temporal-modeling-of-check-ins-in-location-based-social-networks
#2
Ali Zarezade, Sina Jafarzadeh, Hamid R Rabiee
Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users' movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited...
2018: PloS One
https://www.readbyqxmd.com/read/29790097/sex-differences-in-navigation-strategy-and-efficiency
#3
Alexander P Boone, Xinyi Gong, Mary Hegarty
Research on human navigation has indicated that males and females differ in self-reported navigation strategy as well as objective measures of navigation efficiency. In two experiments, we investigated sex differences in navigation strategy and efficiency using an objective measure of strategy, the dual-solution paradigm (DSP; Marchette, Bakker, & Shelton, 2011). Although navigation by shortcuts and learned routes were the primary strategies used in both experiments, as in previous research on the DSP, individuals also utilized route reversals and sometimes found the goal location as a result of wandering...
May 22, 2018: Memory & Cognition
https://www.readbyqxmd.com/read/29789017/leveraging-routine-clinical-materials-and-mobile-technology-to-assess-cbt-fidelity-the-innovative-methods-to-assess-psychotherapy-practices-imapp-study
#4
Shannon Wiltsey Stirman, Luana Marques, Torrey A Creed, Cassidy A Gutner, Robert DeRubeis, Paul G Barnett, Eric Kuhn, Michael Suvak, Jason Owen, Dawne Vogt, Booil Jo, Sonja Schoenwald, Clara Johnson, Kera Mallard, Matthew Beristianos, Heidi La Bash
BACKGROUND: Identifying scalable strategies for assessing fidelity is a key challenge in implementation science. However, for psychosocial interventions, the existing, reliable ways to test treatment fidelity quality are often labor intensive, and less burdensome strategies may not reflect actual clinical practice. Cognitive behavioral therapies (CBTs) provide clinicians with a set of effective core elements to help treat a multitude of disorders, which, evidence suggests, need to be delivered with fidelity to maximize potential client impact...
May 22, 2018: Implementation Science: IS
https://www.readbyqxmd.com/read/29787382/machine-learning-based-dual-energy-ct-parametric-mapping
#5
Kuan-Hao Su, Jung-Wen Kuo, David W Jordan, Steven Van Hedent, Paul Klahr, Zhouping Wei, Rose Al Helo, Fan Liang, Pengjiang Qian, Gisele C Pereira, Negin Rassouli, Robert C Gilkeson, Bryan J Traughber, Chee-Wai Cheng, Raymond F Muzic
The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Z<sub>eff</sub>), relative electron density (ρ<sub>e</sub>), mean excitation energy (<i>I<sub>x</sub></i>), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. 
 Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes...
May 22, 2018: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29785910/a-large-scale-study-of-indicators-of-sub-clinical-mastitis-in-dairy-cattle-by-attribute-weighting-analysis-of-milk-composition-features-highlighting-the-predictive-power-of-lactose-and-electrical-conductivity
#6
Esmaeil Ebrahimie, Faezeh Ebrahimi, Mansour Ebrahimi, Sarah Tomlinson, Kiro R Petrovski
Sub-clinical mastitis (SCM) affects milk composition. In this study, we hypothesise that large-scale mining of milk composition features by pattern recognition models can identify the best predictors of SCM within the milk composition features. To this end, using data mining algorithms, we conducted a large-scale and longitudinal study to evaluate the ability of various milk production parameters as indicators of SCM. SCM is the most prevalent disease of dairy cattle, causing substantial economic loss for the dairy industry...
May 2018: Journal of Dairy Research
https://www.readbyqxmd.com/read/29784820/efficient-collective-swimming-by-harnessing-vortices-through-deep-reinforcement-learning
#7
Siddhartha Verma, Guido Novati, Petros Koumoutsakos
Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fish can improve their sustained propulsive efficiency by placing themselves in appropriate locations in the wake of other swimmers and intercepting judiciously their shed vortices. This swimming strategy leads to collective energy savings and is revealed through a combination of high-fidelity flow simulations with a deep reinforcement learning (RL) algorithm...
May 21, 2018: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29783256/-psychological-features-of-the-motivation-component-in-the-training-of-doctors-in-the-system-of-postgraduate-education
#8
Svitlana Koshova, Viktoriia Horachuk, Valerii Pishchykov
OBJECTIVE: Introduction: Тhe problem of motivating adult learning in postgraduate education has so far been the subject of study primarily in methodological and pedagogical studies. They focus on the analysis of the content side of the motivation of adult learning activities. As for the problem of the dynamics of motivation for adult learning activities, including for doctors in the system of postgraduate medical education with continuous professional development, it has not been sufficiently studied so far...
2018: Wiadomości Lekarskie: Organ Polskiego Towarzystwa Lekarskiego
https://www.readbyqxmd.com/read/29781230/using-language-input-and-lexical-processing-to-predict-vocabulary-size
#9
Tristan Mahr, Jan Edwards
Children learn words by listening to caregivers, and the quantity and quality of early language input predict later language development. Recent research suggests that word recognition efficiency may influence the relationship between input and vocabulary growth. We asked whether language input and lexical processing at 28-39 months predicted vocabulary size one year later in 109 preschoolers. Input was measured using adult word counts from LENA recordings. We used the visual world paradigm and measured lexical processing as the rate of change in proportion of looks to target...
May 20, 2018: Developmental Science
https://www.readbyqxmd.com/read/29779999/peer-assisted-learning-model-enhances-clinical-clerk-s-procedural-skills
#10
Chia-Chang Huang, Hui-Chi Hsu, Ling-Yu Yang, Chen-Huan Chen, Ying-Ying Yang, Ching-Chih Chang, Chiao-Lin Chuang, Wei-Shin Lee, Fa-Yauh Lee, Shinn-Jang Hwang
BACKGROUND: Failure to transfer procedural skills learned in a laboratory to the bedside is commonly due to a lack of peer support/stimulation. A digital platform (Facebook) allows new clinical clerks to share experiences and tips that help augment their procedural skills in a peer-assisted learning/teaching method. This study aims to investigate the effectiveness of the innovation of using the digital platform to support the transfer of laboratory-trained procedural skills in the clinical units...
May 17, 2018: Journal of the Chinese Medical Association: JCMA
https://www.readbyqxmd.com/read/29777359/regulatory-mechanisms-of-thiol-based-redox-sensors-lessons-learned-from-structural-studies-on-prokaryotic-redox-sensors
#11
REVIEW
Sang Jae Lee, Dong-Gyun Kim, Kyu-Yeon Lee, Ji Sung Koo, Bong-Jin Lee
Oxidative stresses, such as reactive oxygen species, reactive electrophilic species, reactive nitrogen species, and reactive chlorine species, can damage cellular components, leading to cellular malfunction and death. In response to oxidative stress, bacteria have evolved redox-responsive sensors that enable them to simultaneously monitor and eradicate potential oxidative stress. Specifically, redox-sensing transcription regulators react to oxidative stress by means of modifying the thiol groups of cysteine residues, functioning as part of an efficient survival mechanism for many bacteria...
May 17, 2018: Archives of Pharmacal Research
https://www.readbyqxmd.com/read/29776841/-medical-simulation-as-a-tool-in-the-training-of-perinatal-professionals
#12
B Tosello, J Blanc, C Kelway, V Pellegrin, E Quarello, F Comte, C Zakarian, C D'Ercole
Though technology plays an increasingly important role in modern health systems, human performance remains a major determinant of safety, effectiveness and efficiency of patient care. This is especially true in the delivery room. Thus, the training of professionals must aim not only for the acquisition of theory and practical skills on an individual basis, but also for the learning of teamwork systematically. Training health professionals with simulation enhances their theoretical knowledge and meets formal requirements in literacy, technical skills and communication...
May 15, 2018: Gynecologie, Obstetrique, Fertilite & Senologie
https://www.readbyqxmd.com/read/29775850/electrical-resistivity-imaging-inversion-an-isfla-trained-kernel-principal-component-wavelet-neural-network-approach
#13
Feibo Jiang, Li Dong, Qianwei Dai
The traditional artificial neural network (ANN) inversion of electrical resistivity imaging (ERI) based on gradient descent algorithm is known to be inept for its low computation efficiency and does not ensure global convergence. In order to solve above problems, a kernel principal component wavelet neural network (KPCWNN) trained by an improved shuffled frog leaping algorithm (ISFLA) method is proposed in this study. An additional kernel principal component (KPC) layer is applied to reduce the dimensionality of apparent resistivity data and increase the computational efficiency of wavelet neural network (WNN)...
April 24, 2018: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/29774599/deep-convolutional-neural-network-for-segmentation-of-knee-joint-anatomy
#14
Zhaoye Zhou, Gengyan Zhao, Richard Kijowski, Fang Liu
PURPOSE: To describe and evaluate a new segmentation method using deep convolutional neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex deformable modeling to improve the efficiency and accuracy of knee joint tissue segmentation. METHODS: A segmentation pipeline was built by combining a semantic segmentation CNN, 3D fully connected CRF, and 3D simplex deformable modeling. A convolutional encoder-decoder network was designed as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification for 12 different joint structures...
May 17, 2018: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/29772818/integrated-method-for-personal-thermal-comfort-assessment-and-optimization-through-users-feedback-iot-and-machine-learning-a-case-study-%C3%A2
#15
Francesco Salamone, Lorenzo Belussi, Cristian Currò, Ludovico Danza, Matteo Ghellere, Giulia Guazzi, Bruno Lenzi, Valentino Megale, Italo Meroni
Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV and PPD) and users as active subjects whose thermal perception is influenced by outdoor climatic conditions (adaptive approach). The latter method is the starting point to investigate thermal comfort from an overall perspective by considering endogenous variables besides the traditional physical and environmental ones...
May 17, 2018: Sensors
https://www.readbyqxmd.com/read/29771997/core-neurological-examination-items-for-neurology-clerks-a-modified-delphi-study-with-a-grass-roots-approach
#16
Chi-Hung Liu, Li-Ling Hsu, Cheng-Ting Hsiao, Suh-Ing Hsieh, Chun-Wei Chang, Elaine Shinwei Huang, Yeu-Jhy Chang
BACKGROUND: With the evolution of treatments for neurological diseases, the contents of core neurological examinations (NEs) for medical students may need to be modified. We aimed to establish a consensus on the core NE items for neurology clerks and compare viewpoints between different groups of panelists. METHODS: First, a pilot group proposed the core contents of NEs for neurology clerks. The proposed core NE items were then subject to a modified web-based Delphi process using the online software "SurveyMonkey"...
2018: PloS One
https://www.readbyqxmd.com/read/29771811/use-of-emergency-manuals-during-actual-critical-events-in-china-a-multi-institutional-study
#17
Jeffrey Huang, Jiayan Wu, Christina Dai, Xianwei Zhang, Hui Ju, Yiqi Chen, Chunyuan Zhang, Fan Ye, Yi Tan, Yongbo Zong, Telong Liu
INTRODUCTION: Emergency manuals (EMs) can help healthcare providers respond to crises more efficiently. Three anesthesia EMs have been translated into Chinese. These EMs have been made publicly available as a free document downloadable in China. A year after these Chinese versions of EMs were published, we conducted a multi-institutional survey in China to assess the progress of how well EM had been adapted and used in the setting of critical events. METHODS: Our study used a multi-institutional, anonymous electronic survey...
May 16, 2018: Simulation in Healthcare: Journal of the Society for Simulation in Healthcare
https://www.readbyqxmd.com/read/29771676/extreme-trust-region-policy-optimization-for-active-object-recognition
#18
Huaping Liu, Yupei Wu, Fuchun Sun
In this brief, we develop a deep reinforcement learning method to actively recognize objects by choosing a sequence of actions for an active camera that helps to discriminate between the objects. The method is realized using trust region policy optimization, in which the policy is realized by an extreme learning machine and, therefore, leads to efficient optimization algorithm. The experimental results on the publicly available data set show the advantages of the developed extreme trust region optimization method...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771675/action-driven-visual-object-tracking-with-deep-reinforcement-learning
#19
Sangdoo Yun, Jongwon Choi, Youngjoon Yoo, Kimin Yun, Jin Young Choi
In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771674/multisource-transfer-double-dqn-based-on-actor-learning
#20
Jie Pan, Xuesong Wang, Yuhu Cheng, Qiang Yu
Deep reinforcement learning (RL) comprehensively uses the psychological mechanisms of "trial and error" and "reward and punishment" in RL as well as powerful feature expression and nonlinear mapping in deep learning. Currently, it plays an essential role in the fields of artificial intelligence and machine learning. Since an RL agent needs to constantly interact with its surroundings, the deep Q network (DQN) is inevitably faced with the need to learn numerous network parameters, which results in low learning efficiency...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
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