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4th IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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5th International Conference on Variable Neighborhood Search (ICVNS'17)

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Electronic Notes in Discrete Mathematics 2018年 66卷 1-5页

作者： Vitor Nazário Coelho Haroldo Gambini Santos Igor Machado Coelho Puca Huachi Vaz Penna Thays A. Oliveira Marcone Jamilson Freitas Souza Angelo Sifaleras Institute of Computer Science Universidade Federal Fluminense Niterói Brazil Grupo da Causa Humana Ouro Preto Brazil Department of Computing Universidade Federal de Ouro Preto Ouro Preto Brazil Institute of Mathematics Statitics Universidade Estadual do Rio de Janeiro Rio de Janeiro Brazil Graduate Program of the Department of Engineering and Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Department of Applied Informatics School of Information Sciences University of Macedonia 156 Egnatia Str. Thessaloniki 54636 Greece

This volume presents selected, peer-reviewed, short papers that were accepted for presentation in the 5th International Conference on Variable Neighborhood Search (ICVNS'17) which was held in Ouro Preto, Brazil, d... 详细信息

关键词： Metaheuristics Variable Neighborhood Search Discrete Optimization Nonlinear optimization

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Magnetic-free nonreciprocal photonic platform based on time-modulated graphene capacitors

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Physical Review B 2018年第16期98卷 165428-165428页

作者： D. Correas-Serrano A. Alù J. S. Gomez-Diaz Department of Electrical and Computer Engineering University of California Davis One Shields Avenue Kemper Hall 2039 Davis California 95616 USA Photonics Initiative Advanced Science Research Center City University of New York 85 St. Nicholas Terrace New York City New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA and Department of Electrical Engineering City College of the City University of New York New York New York 10031 USA

We propose a paradigm for the realization of nonreciprocal photonic devices based on time-modulated graphene capacitors coupled to photonic waveguides, without relying on magneto-optic effects. The resulting hybrid graphene-dielectric platform is low loss, silicon compatible, robust against graphene imperfections, scalable from terahertz to near-infrared frequencies, and it exhibits large nonreciprocal responses using realistic biasing schemes. We introduce an analytical framework based on solving the eigenstates of the modulated structure and on spatial coupled mode theory, unveiling the physical mechanisms that enable nonreciprocity and enabling a quick analysis and design of optimal isolator geometries based on synthetic linear and angular momentum bias. Our results, validated through harmonic-balance full-wave simulations, confirm the feasibility of the introduced low-loss (<3 dB) platform to realize large photonic isolation through various mechanisms, such as narrow-band asymmetric band gaps and interband photonic transitions that allow multiple isolation frequencies and large bandwidths. We envision that this technology may pave the wave to magnetic-free, fully integrated, and CMOS–compatible nonreciprocal components with wide applications in photonic networks and thermal management.

关键词： Photonics Plasmonics Graphene Waveguides Lorentz symmetry

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Nanophotonic engineering of far-field thermal emitters

arXiv

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arXiv 2018年

作者： Baranov, Denis G. Xiao, Yuzhe Nechepurenko, Igor A. Krasnok, Alex Alù, Andrea Kats, Mikhail A. Department of Physics Chalmers University of Technology Gothenburg412 96 Sweden Department of Electrical and Computer Engineering University of Wisconsin-Madison WI United States Dukhov Research Institute of Automatics 22 Sushchevskaya Moscow127055 Russia Photonics Initiative Advanced Science Research Center City University of New York NY10031 United States Physics Program Graduate Center City University of New York NY10016 United States Department of Electrical Engineering City College of The City University of New York New York10031 United States Department of Materials Science and Engineering University of Wisconsin-Madison WI United States Department of Physics University of Wisconsin-Madison WI United States

Thermal emission is a ubiquitous and fundamental process by which all objects at non-zero temperatures radiate electromagnetic energy. This process is often presented to be incoherent in both space and time, resulting in broadband, omnidirectional light emission toward the far field, with a spectral density related to the emitter temperature by Planck’s law. Over the past two decades, there has been considerable progress in engineering the spectrum, directionality, polarization, and temporal response of thermally emitted light using nanostructured materials. This review summarizes the basic physics of thermal emission, lays out various nanophotonic approaches to engineer thermal-emission in the far field, and highlights several relevant applications, including energy harvesting, lighting, and radiative cooling. Copyright © 2018, The Authors. All rights reserved.

关键词： Spectral density

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Functional annotation of chemical libraries across diverse biological processes (vol 13, pg 982, 2017)

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NATURE CHEMICAL BIOLOGY 2017年第12期13卷 1286-1286页

作者： Piotrowski, Jeff S. Li, Sheena C. Deshpande, Raamesh Simpkins, Scott W. Nelson, Justin Yashiroda, Yoko Barber, Jacqueline M. Safizadeh, Hamid Wilson, Erin Okada, Hiroki Gebre, Abraham A. Kubo, Karen Torres, Nikko P. LeBlanc, Marissa A. Andrusiak, Kerry Okamoto, Reika Yoshimura, Mami DeRango-Adem, Eva van Leeuwen, Jolanda Shirahige, Katsuhiko Baryshnikova, Anastasia Brown, Grant W. Hirano, Hiroyuki Costanzo, Michael Andrews, Brenda Ohya, Yoshikazu Osada, Hiroyuki Yoshida, Minoru Myers, Chad L. Boone, Charles RIKEN Center for Sustainable Resource Science Wako Saitama Japan. Department of Computer Science and Engineering University of Minnesota-Twin Cities Minneapolis Minnesota USA. Bioinformatics and Computational Biology Program University of Minnesota-Twin Cities Minneapolis Minnesota USA. Department of Electrical and Computer Engineering University of Minnesota-Twin Cities Minneapolis Minnesota USA. Department of Integrated Biosciences Graduate School of Frontier Sciences University of Tokyo Kashiwa Chiba Japan. Donnelly Centre University of Toronto Toronto Ontario Canada. Institute of Molecular and Cellular Biosciences Center for Epigenetic Disease University of Tokyo Bunkyo-ku Tokyo Japan. Lewis-Sigler Institute for Integrative Genomics Princeton University Princeton New Jersey USA. Department of Biochemistry University of Toronto Toronto Ontario Canada.

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

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Investigation of the visual attention role in clinical bioethics decision-making using machine learning algorithms

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Procedia computer science 2017年 108卷 1165-1174页

作者： Daniel L. Fernandes Rodrigo Siqueira-Batista Andréia P. Gomes Camila R. Souza Israel T. da Costa Felippe da S.L. Cardoso João V. de Assis Gustavo H.L. Caetano Fabio R. Cerqueira Graduate Program in Computer Science Universidade Federal de Viçosa Minas Gerais Brazil Department of Medicine and Nursing Universidade Federal de Viçosa Minas Gerais Brazil Department of Physical Education Universidade Federal de Viçosa Minas Gerais Brazil Department of Production Engineering Universidade Federal Fluminense Rio de Janeiro Brazil

This study proposes the use of a computational approach based on machine learning (ML) algorithms to build predictive models using eye tracking data. Our intention is to provide results that may support the study of medical investigation in the decision-making process in clinical bioethics, particularly in this work, in cases of euthanasia. The data used in the approach were collected from 75 students of the nursing undergraduate course using an eye tracker. The available data were processed through feature selection methods, and were later used to create models capable of predicting the euthanasia decision through ML algorithms. Statistical experiments showed that the predictive model resultant from the multilayer perceptron (MLP) algorithm led to the best performance compared with the other tested algorithms, presenting an accuracy of 90.7% and a mean area under the ROC curve of 0.90. Interesting knowledge (patterns and rules) for the studied bioethical decision-making was extracted using simulations with MLP models and inspecting the obtained decision-tree rules. The good performance shown by the obtained MLP predictive model demonstrates that the proposed investigation approach may be used to test scientific hypotheses related to visual attention and decision-making.

关键词： Visual attention Decision-making in bioethics Mobile eye tracking Machine learning in medicine

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Highly accurate model for prediction of lung nodule malignancy with ct scans

arXiv

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arXiv 2018年

作者： Causey, Jason Zhang, Junyu Ma, Shiqian Jiang, Bo Qualls, Jake Politte, David G. Prior, Fred Zhang, Shuzhong Huang, Xiuzhen Department of Computer Science Arkansas State University JonesboroAR72467 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin N.T. Hong Kong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Mallinckrodt Institute of Radiology Washington University St. LouisMO63110 United States Department of Biomedical Informatics University of Arkansas for Medical Sciences Little RockAR72205 United States UALR/UAMS Joint Graduate Program in Bioinformatics Little RockAR72204 United States

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://***/NoduleX. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Author Correction: Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

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Nature genetics 2023年第6期55卷 1080页

作者： Bernardo Rodriguez-Martin Eva G Alvarez Adrian Baez-Ortega Jorge Zamora Fran Supek Jonas Demeulemeester Martin Santamarina Young Seok Ju Javier Temes Daniel Garcia-Souto Harald Detering Yilong Li Jorge Rodriguez-Castro Ana Dueso-Barroso Alicia L Bruzos Stefan C Dentro Miguel G Blanco Gianmarco Contino Daniel Ardeljan Marta Tojo Nicola D Roberts Sonia Zumalave Paul A Edwards Joachim Weischenfeldt Montserrat Puiggròs Zechen Chong Ken Chen Eunjung Alice Lee Jeremiah A Wala Keiran M Raine Adam Butler Sebastian M Waszak Fabio C P Navarro Steven E Schumacher Jean Monlong Francesco Maura Niccolo Bolli Guillaume Bourque Mark Gerstein Peter J Park David C Wedge Rameen Beroukhim David Torrents Jan O Korbel Iñigo Martincorena Rebecca C Fitzgerald Peter Van Loo Haig H Kazazian Kathleen H Burns Peter J Campbell Jose M C Tubio Department of Zoology Genetics and Physical Anthropology Universidade de Santiago de Compostela Santiago de Compostela Spain. Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain. Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain. Transmissible Cancer Group Department of Veterinary Medicine University of Cambridge Cambridge UK. The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain. Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK. Genome Data Science Institute for Research in Biomedicine (IRB Barcelona) The Barcelona Institute of Science and Technology (BIST) Barcelona Spain. Institucio Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain. The Francis Crick Institute London UK. Department of Human Genetics University of Leuven Leuven Belgium. Genomes and Disease Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon South Korea. Cancer Ageing and Somatic Mutation Programme Wellcome Sanger Institute Cambridge UK. Department of Biochemistry Genetics and Immunology University of Vigo Vigo Spain. Galicia Sur Health Research Institute Vigo Spain. Faculty of Science and Technology University of Vic-Central University of Catalonia (UVic-UCC) Vic Spain. Barcelona Supercomputing Center (BSC) Barcelona Spain. Experimental Cancer Genetics Wellcome Sanger Institute Cambridge UK. Oxford Big Data Institute University of Oxford Oxford UK. DNA Repair and Genome Integrity Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain. Department of Biochemistry and Molecular Biology Universidade de Santiago de Compostela Santiago de Compostela Spain. Medical R

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Wildlife-microbiome interactions and disease: exploring opportunities for disease mitigation across ecological scales

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Drug Discovery Today: Disease Models 2018年 28卷 105-115页

作者： Williams, Candace L. Caraballo-Rodríguez, Andrés Mauricio Allaband, Celeste Zarrinpar, Amir Knight, Rob Gauglitz, Julia M. Institute for Conservation Research San Diego Zoo Global United States Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California La Jolla San Diego 92307 CA United States Biomedical Sciences Graduate Program University of California La Jolla San Diego 92307 CA United States Department of Medicine University of California La Jolla San Diego 92307 CA United States Veterans Affairs San Diego Healthcare System San Diego California University of California La Jolla San Diego 92307 CA United States Department of Pediatrics University of California La Jolla San Diego 92037 CA United States Department of Bioengineering University of California La Jolla San Diego 92093 CA United States Department of Computer Science and Engineering University of California La Jolla San Diego 92093 CA United States Center for Microbiome Innovation University of California La Jolla San Diego 92307 CA United States

Captive wildlife are a unique set of animals, whose diverse host–microbe symbioses are underexplored. Compared to their wild counterparts they are particularly susceptible to a variety of diseases, many of which have explicit or purported links to the microbiome. In this perspective, we will examine how the microbiome influences gastrointestinal disorders, metabolic dysregulation, reproduction, and disease susceptibility in captive wildlife. Investigation of wildlife, and specifically captive wildlife, affords a unique opportunity to gain understanding of the broad diversity of the associated microbiota and learn from nature's molecular and microbial responses to disease. Studies like these could lead to the discovery of new interventions, ranging from dietary changes to the use of microbes or their natural products as treatment. Intervention strategies can lead to the discovery of medically relevant small molecules and the development of a novel platform for N-of-1 targeted medical investigations. © 2019 Elsevier Ltd

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Author Correction: Effect of de novo transcriptome assembly on transcript quantification

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Scientific reports 2019年第1期9卷 18041页

作者： Ping-Han Hsieh Yen-Jen Oyang Chien-Yu Chen Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei 10617 Taiwan. Department of Computer Science and Information Engineering National Taiwan University Taipei 10617 Taiwan. Department of Bio-Industrial Mechatronics Engineering National Taiwan University Taipei 10617 Taiwan. chienyuchen@ntu.edu.tw. Genome and Systems Biology Program National Taiwan University and Academia sinica Taipei 10617 Taiwan. chienyuchen@ntu.edu.tw.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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