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Annual IEEE Symposium on computer-Based Medical Systems

作者： Leila C.C. Bergamasco Hellyan Oliveira Helton Bíscaro Harry Wechsler Fátima L.S. Nunes Polytechnic School - Graduate Program in Electrical Engineering University of Sao Paulo São Paulo SP Brasil Laboratory of Health Informatics Applications University of Sao Paulo São Paulo SP Brasil Department of Computer Science George Mason University Fairfax VA USA

Three-dimensional models have been used to aid medical diagnoses, using images generated by modalities like Magnetic Resonance Imaging. They can provide a more complete vision of objects since their depth is taken into account. Content-based Image Retrieval (CBIR) has also been used to aid the diagnosis. One important step in Three-dimensional CBIR (Model Retrieva) systems is the comparison between two models by using a set of features extracted and stored in a database. In this paper we present a novel method to compare two models, using the Bipartite graphs technique, with the aim to improve the retrieval precision. This technique retrieves 3D medical models of the left ventricle in order to aid the diagnosis of Congestive Heart Failure. Results showed that the novel method improved the precision by 10% when compared to the Similarity Function of Euclidean and Manhattan distance. These results confirmed that bipartite graph techniques can be used to improve the accuracy of Model Retrieval systems.

关键词： Solid modeling Three-dimensional displays Computational modeling Medical diagnostic imaging Feature extraction Bipartite graph

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Fat percentage equation for children with cerebral palsy: A novel approach

Fat percentage equation for children with cerebral palsy: A ...

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13th Mediterranean Conference on Medical and Biological engineering and Computing 2013, MEDICON 2013

作者： Neves, E.B. Krueger, E. Rosário, B.R. Oliveira, M.C.N. Pol, S. Ripka, W.L. Campos de Andrade University Center Vitória Research Center Curitiba Brazil Federal Technological University of Paraná Graduate Program in Electrical Engineering and Computer Science Curitiba Brazil Federal Technological University of Paraná Graduate Program in Biomedical Engineering Curitiba Brazil

ISBN: (纸本)9783319008455

Nutritional changes are commonly related to children with cerebral palsy (CP), since these are problems as: dysphagia, vomiting and gastrointestinal reflux. For nutritional monitoring, body composition has become an important tool and has been present in this population assessments routine. In this sense, the aim of this study was to develop an equation for body composition estimate for children with cerebral palsy, aged between 5 and 6 years, using skinfolds, from the results of body composition obtained by Dual Energy X-rays Absormetry (DEXA). The study included 10 male children with cerebral palsy, aged between five and six-years-old, who participated in the physical therapy intensive program in Vitória research center, Curitiba, Brazil. Participants were assessed by: the Gross Motor Function Classification System;DEXA;and skinfold thickness. The skinfolds that showed better correlation with the total fat percentage and segmental fat percentage were: biceps and abdominal. The results of the regression analysis obtained equations to estimate the fat percentage by skinfold thickness with R2: 1.000 and 0.971, to seven and two skinfold thickness, respectively. In this sense, it is recommended to use the equation that utilizes the biceps and abdominal skinfolds thickness to estimate fat percentage of children with cerebral palsy, as this presents good estimation indicators. © Springer International Publishing Swit zerland 2014.

关键词： Biochemistry

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Galvanotactic control of collective cell migration in epithelial monolayers (vol 13, pg 409, 2014)

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NATURE MATERIALS 2014年第5期13卷 530-530页

作者： Cohen, Daniel J. Nelson, W. James Maharbiz, Michel M. Joint Graduate Program in Bioengineering University of California at Berkeley Berkeley California 94720 USA Department of Biology Molelcular Cellular Physiology Stanford University Stanford California 94305 USA Department of Electrical Engineering Computer Science University of California at Berkeley Berkeley California 94720 USA

Many normal and pathological biological processes involve the migration of epithelial cell sheets. This arises from complex emergent behaviour resulting from the interplay between cellular signalling networks and the forces that physically couple the cells. Here, we demonstrate that collective migration of an epithelium can be interactively guided by applying electric fields that bias the underlying signalling networks. We show that complex, spatiotemporal cues are locally interpreted by the epithelium, resulting in rapid, coordinated responses such as a collective U-turn, divergent migration, and unchecked migration against an obstacle. We observed that the degree of external control depends on the size and shape of the cell population, and on the existence of physical coupling between cells. Together, our results offer design and engineering principles for the rational manipulation of the collective behaviour and material properties of a tissue.

关键词： CELL migration EPITHELIUM EPITHELIAL cells CELL populations SPATIOTEMPORAL processes

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Parametric sensitivity analysis of cOptBees optimal clustering algorithm 14

Parametric sensitivity analysis of cOptBees optimal clusteri...

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2014 14th International Conference on Intelligent Systems Design and Applications, ISDA 2014

作者： Cruz, Dávila Patrícia Ferreira Maia, Renato Dourado De Castro, Leandro Nunes Graduate Program in Electrical Engineering Mackenzie University São Paulo Brazil Computer Science Department State University of Montes Claros Montes Claros MG Brazil

ISBN: (纸本)9781479979387

Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning objects into groups or clusters, such that objects in the same group are more similar to one another than to objects belonging to other groups. Many algorithms to solve data clustering problems have been presented in the literature. Recently, bee-inspired clustering algorithms have been proposed, presenting good performance to find groups in data. This paper aims to present the parametric sensitivity analysis of cOptBees, a bee-inspired clustering algorithm designed to find optimal clusters in datasets. The algorithm was run for different parameter configurations to assess the influence of each parameter in its performance. © 2014 IEEE.

关键词： Clustering algorithms

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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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Single-cell morphological analysis for rapid antimicrobial susceptibility test

Single-cell morphological analysis for rapid antimicrobial s...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： J. Choi J. Yoo M. Lee E.-G. Kim J. S. Lee S. Lee S. Joo S. H. Song E.-C. Kim J. C. Lee H. C. Kim Y.-G. Jung S. Kwon Department of Electrical Engineering and Computer Science Seoul National University Seoul Republic of Korea QuantaMatrix Inc. Republic of Korea Interdisciplinary Program of Bioengineering Seoul National University Graduate School Seoul Republic of Korea Department of Laboratory Medicine School of Medicine” Incheon Republic of Korea Department of Laboratory Medicine Seoul National-University Hospital Seoul Republic of Korea Institute of Medical and Biological Engineering Seoul National University Seoul Republic of Korea

A rapid antibiotic susceptibility test (AST) is desperately needed in clinical settings for fast and appropriate antibiotic administration. Traditional ASTs, which rely on cell culture, are not suitable for urgent cases of bacterial infection and antibiotic resistance owing to their relatively long test times. Here, we describe a novel AST called single-cell morphological analysis (SCMA) that can determine antimicrobial susceptibility by automatically analyzing and categorizing morphological changes in single bacterial cells under various antimicrobial conditions. The SCMA was tested with four Clinical and Laboratory Standards Institute standard bacterial strains and 189 clinical samples from hospitals. The results were compared with the gold standard broth microdilution test. The SCMA results were obtained in less than 4 hours with 91.5% categorical agreement and 6.51% minor, 2.56% major, and 1.49% very major discrepancies. Thus, SCMA provides rapid and accurate antimicrobial susceptibility data.

关键词： Microorganisms Antibiotics Strain Immune system Microfluidics Standards Imaging

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Dirichlet tessellation for high-dimensional RSS clustering in Wi-Fi environment

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ICIC Express Letters 2014年第7期8卷 2043-2048页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nanan District Chongqing 400065 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunication and Networking Program School of Information Science University of Pittsburgh PA 15260 United States

The received signal strength (RSS) clustering has played a significant role in site surveying and data pre-processing for the location tracking in Wi-Fi environment. To this end, this paper presents a novel clustering algorithm to cluster the raw RSS vectors with large similarities in both the RSS and physical locations together. The clusters of RSS vectors are determined by the cells which are generated by the Dirichlet tessellation in a transformed low-dimensional space. Our algorithm consists of two steps. We first use the Laplacian embedding to transform the raw measurements into a low-dimensional space, while preserving the RSS and location neighborhood relations. Second, after the seeds of cells are carefully selected, we will tessellate the low-dimensional space by the Dirichlet cells to obtain the clustering results. The experiments conducted in an actual public Wi-Fi environment prove that our algorithm can achieve the smallest cluster scattering in both the RSS and locations compared with the existing affinity propagation clustering, K-means clustering and binary support vector classifier (SVC) algorithms. © 2014 ISSN 1881-803X.

关键词： Wi-Fi

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Metadata Correction: Importance-Performance Analysis of Personal Health Records in Taiwan: A Web-Based Survey

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Journal of medical Internet research 2017年第6期19卷 e209页

作者： Hsiao-Hsien Rau Yi-Syuan Wu Chi-Ming Chu Fu-Chung Wang Min-Huei Hsu Chi-Wen Chang Kang-Hua Chen Yen-Liang Lee Senyeong Kao Yu-Lung Chiu Hsyien-Chia Wen Anis Fuad Chien-Yeh Hsu Hung-Wen Chiu Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan. Administration Department Healthconn Corp Taipei Taiwan. Institute of Medical Informatics Department of Computer Science of Information Engineering National Cheng Kung University Tainan Taiwan. School Of Public Health National Defense Medical Center Taiepi Taiwan. National Health Insurance Administration Ministry of Health and Welfare Taiepi Taiwan. School of Nursing College of Medicine Chang Gung University Linkou Taiwan. Division of Endocrinology Department of Pediatrics Linkou Chang Gung Memorial Hospital Linkou Taiwan. Internet of Things Laboratory Chunghwa Telecom Laboratories TaoYuen Taiwan. School of Health Care Administration Taipei Medical University Taipei Taiwan. Department of Biostatistics Epidemiology and Population Health Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia. Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan. Master Program in Global Health and Development Taipei Medical University Taipei Taiwan.

[This corrects the article DOI: .].

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Construction of time-stamped mobility map for path tracking via smith-waterman measurement matching

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Mathematical Problems in engineering 2014年第1期2014卷 1-17页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Wu, Haibo Pu, Qiaolin Yu, Xiang Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States China Internet Research Lab Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

Path tracking in wireless and mobile environments is a fundamental technology for ubiquitous location-based services (LBSs). In particular, it is very challenging to develop highly accurate and cost-efficient tracking systems applied to the anonymous areas where the floor plans are not available for security and privacy reasons. This paper proposes a novel path tracking approach for large Wi-Fi areas based on the time-stamped unlabeled mobility map which is constructed from Smith-Waterman received signal strength (RSS) measurement matching. Instead of conventional location fingerprinting, we construct mobility map with the technique of dimension reduction from the raw measurement space into a low-dimensional embedded manifold. The feasibility of our proposed approach is verified by the real-world experiments in the HKUST campus Wi-Fi networks, sMobileNet. The experimental results prove that our approach is adaptive and capable of achieving an adequate precision level in path tracking. © 2014 Mu Zhou et al.

关键词： Wi-Fi

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Floor plan construction via anonymous Wi-Fi signal fragment matching

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ICIC Express Letters, Part B: Applications 2014年第4期5卷 981-987页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Wang, Zhuoran Chongqing Key Lab of Mobile Communications Technology School of Communication and Information Engineering Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nan'an Dist. Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh PA 15260 United States

Floor plan construction is the basis for fingerprint-based localization and people's activity learning, especially in the environments where the geometrical map is not available or does not exist. To this end, we propose a new received signal strength (RSS) fragment matching approach to identify the location points (LPs) in floor plan as the overlapped pieces between the fragments. Then, by means of the Smith-Waterman alignment, each LP can be recognized as a winning path in scoring space. Finally, we use the Allen's interval algebra to assemble the time-stamped LPs into a floor plan in target area. The experiments with the actual Wi-Fi RSS measurements recorded in HKUST campus demonstrate that our proposed approach performs better than the conventional K-means clustering and spectral clustering in floor plan construction. © 2014 ICIC International.

关键词： Algebra

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