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Dense sampling of bird diversity increases power of comparative genomics (vol 587, pg 252, 2020)

NATURE 2021年第7856期592卷 E24-E24页

作者： Feng, Shaohong Stiller, Josefin Deng, Yuan Armstrong, Joel Fang, Qi Reeve, Andrew Hart Xie, Duo Chen, Guangji Guo, Chunxue Faircloth, Brant C. Petersen, Bent Wang, Zongji Zhou, Qi Diekhans, Mark Chen, Wanjun Andreu-Sanchez, Sergio Margaryan, Ashot Howard, Jason Travis Parent, Carole Pacheco, George Sinding, Mikkel-Holger S. Puetz, Lara Cavill, Emily Ribeiro, Angela M. Eckhart, Leopold Fjeldsa, Jon Hosner, Peter A. Brumfield, Robb T. Christidis, Les Bertelsen, Mads F. Sicheritz-Ponten, Thomas Tietze, Dieter Thomas Robertson, Bruce C. Song, Gang Borgia, Gerald Claramunt, Santiago Lovette, Irby J. Cowen, Saul J. Njoroge, Peter Dumbacher, John Philip Ryder, Oliver A. Fuchs, Jerome Bunce, Michael Burt, David W. Cracraft, Joel Meng, Guanliang Hackett, Shannon J. Ryan, Peter G. Jonsson, Knud Andreas Jamieson, Ian G. da Fonseca, Rute R. Braun, Edward L. Houde, Peter Mirarab, Siavash Suh, Alexander Hansson, Bengt Ponnikas, Suvi Sigeman, Hanna Stervander, Martin Frandsen, Paul B. van der Zwan, Henriette van der Sluis, Rencia Visser, Carina Balakrishnan, Christopher N. Clark, Andrew G. Fitzpatrick, John W. Bowman, Reed Chen, Nancy Cloutier, Alison Sackton, Timothy B. Edwards, Scott V. Foote, Dustin J. Shakya, Subir B. Sheldon, Frederick H. Vignal, Alain Soares, Andre E. R. Shapiro, Beth Gonzalez-Solis, Jacob Ferrer-Obiol, Joan Rozas, Julio Riutort, Marta Tigano, Anna Friesen, Vicki Dalen, Love Urrutia, Araxi O. Szekely, Tamas Liu, Yang Campana, Michael G. Corvelo, Andre Fleischer, Robert C. Rutherford, Kim M. Gemmell, Neil J. Dussex, Nicolas Mouritsen, Henrik Thiele, Nadine Delmore, Kira Liedvogel, Miriam Franke, Andre Hoeppner, Marc P. Krone, Oliver Fudickar, Adam M. Mila, Borja Ketterson, Ellen D. Fidler, Andrew Eric Friis, Guillermo Parody-Merino, Angela M. Battley, Phil F. Cox, Murray P. Lima, Nicholas Costa Barroso Prosdocimi, Francisco Parchman, Thomas Lee Schlinger, Barney A. Loiselle, Bette A. Blake, John G. Lim, Haw Chuan Day, Lainy B. Fuxjager, Matthew J. Baldwin, Maude W. Braun, Michael J. Wirthlin, Morgan Dikow, China National GeneBank BGI-Shenzhen Shenzhen China State Key Laboratory of Genetic Resources and Evolution Kunming Institute of Zoology Chinese Academy of Sciences Kunming China BGI-Shenzhen Shenzhen China Villum Centre for Biodiversity Genomics Section for Ecology and Evolution Department of Biology University of Copenhagen Copenhagen Denmark BGI Education Center University of Chinese Academy of Sciences Shenzhen China MOE Laboratory of Biosystems Homeostasis and Protection Life Sciences Institute Zhejiang University Hangzhou China Department of Neuroscience and Developmental Biology University of Vienna Vienna Austria Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming China James D. Watson Institute of Genome Sciences Hangzhou China UC Santa Cruz Genomics Institute UC Santa Cruz Santa Cruz CA USA Natural History Museum of Denmark University of Copenhagen Copenhagen Denmark Center for Macroecology Evolution and Climate GLOBE Institute University of Copenhagen Copenhagen Denmark Department of Biological Sciences Louisiana State University Baton Rouge LA USA Museum of Natural Science Louisiana State University Baton Rouge LA USA Centre of Excellence for Omics-Driven Computational Biodiscovery (COMBio) Faculty of Applied Sciences AIMST University Kedah Malaysia Section for Evolutionary Genomics The GLOBE Institute Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Institute of Molecular Biology National Academy of Sciences Yerevan Armenia University Museum Norwegian University of Science and Technology Trondheim Norway Center for Reproductive Medicine The 2nd Affiliated Hospital School of Medicine Zhejiang University Hangzhou China Novogene Durham NC USA Duke University Medical Center Durham NC USA The Rockefeller University New York NY USA Howard Hughes Medical Institute Chevy Chase MD USA Department of Dermatology Medical University of Vienna Vienna Austria

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Accelerating internet penetration to rural areas: A government-sponsored internet-kiosks deployment project in Garut Regency, West Java of Indonesia 9

Accelerating internet penetration to rural areas: A governme...

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9th International Conference on Telecommunication Systems Services and Applications, TSSA 2015

作者： Kurniawan, A. Zakia, I. Wartika, E. Austin, A.G. School of Electrical Engineering and Informatics Institut Teknologi Bandung Jalan Ganeca 10 Bandung40132 Indonesia Study Program of Film and Television Institut Seni Budaya Bandung Jalan Buahbatu 212 Bandung40265 Indonesia Faculty of Civil Engineering and Environment Institut Teknologi Bandung Jalan Ganeca 10 Bandung40132 Indonesia

ISBN: (纸本)9781467384469

Internet penetration in developing countries depend on a variety of factors, including the Gross Domestic Product (GDP), the density of telephone connections, and the density of personal computer users. Internet kiosks have been deployed in 21 rural ditrict areas of Garut Regency to facilitate internet access for local/district government as well as for the community who have no access to internet. Each district was equiped with 10 PCs, a printer, a scanner, and an internet connection either using DSL or cellular access technology. The program was government sponsored through the Ministry of Communications and information of the Republic of Indonesia. This program was also designed to provide education and training for the district internet kiosks operator as well as for the staffs of information technology at Garut Regency, on understanding, efficient use, management, maintenance, as well as the ethical/professional use of information to upgrade their skills. This study was then conducted to evaluate factors affecting internet penetration in rural areas of Garut Regency, West Java of Indonesia. © 2015 IEEE.

关键词： Demography

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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM_2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease study 2019

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The Lancet Planetary Health 2022年第7期6卷 e586-e600页

作者： Burkart, Katrin Causey, Kate Cohen, Aaron J Wozniak, Sarah S Salvi, Devashri Digvijay Abbafati, Cristiana Adekanmbi, Victor Adsuar, Jose C Ahmadi, Keivan Alahdab, Fares Al-Aly, Ziyad Alipour, Vahid Alvis-Guzman, Nelson Amegah, Adeladza Kofi Andrei, Catalina Liliana Andrei, Tudorel Ansari, Fereshteh Arabloo, Jalal Aremu, Olatunde Aripov, Timur Babaee, Ebrahim Banach, MacIej Barnett, Anthony Bärnighausen, Till Winfried Bedi, Neeraj Behzadifar, Masoud Béjot, Yannick Bennett, Derrick A Bensenor, Isabela M Bernstein, Robert S Bhattacharyya, Krittika Bijani, Ali Biondi, Antonio Bohlouli, Somayeh Breitner, Susanne Brenner, Hermann Butt, Zahid A Cámera, Luis Alberto Cantu-Brito, Carlos Carvalho, Felix Cerin, Ester Chattu, Vijay Kumar Chauhan, Bal Govind Choi, Jee-Young Jasmine Chu, Dinh-Toi Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Daryani, Ahmad Davletov, Kairat De Courten, Barbora Demeke, Feleke Mekonnen Denova-Gutiérrez, Edgar Dharmaratne, Samath Dhamminda Dhimal, Meghnath Diaz, Daniel Djalalinia, Shirin Duncan, Bruce B El Sayed Zaki, Maysaa Eskandarieh, Sharareh Fareed, Mohammad Farzadfar, Farshad Fattahi, Nazir Fazlzadeh, Mehdi Fernandes, Eduarda Filip, Irina Fischer, Florian Foigt, Nataliya A Freitas, Marisa Ghashghaee, Ahmad Gill, Paramjit Singh Ginawi, Ibrahim Abdelmageed Gopalani, Sameer Vali Guo, Yuming Gupta, Rajat Das Habtewold, Tesfa Dejenie Hamadeh, Randah R Hamidi, Samer Hankey, Graeme J Hasanpoor, Edris Hassen, Hamid Yimam Hay, Simon I Heibati, Behzad Hole, Michael K Hossain, Naznin Househ, Mowafa Irvani, Seyed Sina Naghibi Jaafari, Jalil Jakovljevic, Mihajlo Jha, Ravi Prakash Jonas, Jost B Jozwiak, Jacek Jerzy Kasaeian, Amir Kaydi, Neda Khader, Yousef Saleh Khafaie, Morteza Abdullatif Khan, Ejaz Ahmad Khan, Junaid Khan, Md Nuruzzaman Khatab, Khaled Khater, Amir M Kim, Yun Jin Kimokoti, Ruth W Kisa, Adnan Kivimäki, Mika Knibbs, Luke D Kosen, Soewarta Koul, Parvaiz A Koyanagi, Ai Defo, Barthelemy Kuate Kugbey, Nuworza Lauriola, Paolo Lee, Paul H Leili, Mostafa Lewycka, Sonia Li, Shanshan Lim, Lee-Ling Li Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Plastic and Reconstructive Surgery University of Washington Seattle WA United States Research Insights and Innovation Seattle WA United States Health Effects Institute Boston MA United States School of Public Health Boston University Boston MA United States Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Population Medicine Cardiff University Cardiff United Kingdom Sport Science Department University of Extremadura Badajoz Spain School of Public Health Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center US Department of Veterans Affairs (VA) St Louis MO United States Health Management and Economics Research Center Iran University of Medical Sciences Tehran Iran Department of Health Economics Iran University of Medical Sciences Tehran Iran Preventive Medicine and Public Health Research Center Iran University of Medical Sciences Tehran Iran Pars Advanced and Minimally Invasive Medical Manners Research Center Iran University of Medical Sciences Tehran Iran Department of Community and Family Medicine Iran University of Medical Sciences Tehran Iran Research Group in Hospital Management and Health Policies Universidad de la Costa (University of the Coast) Barranquilla Colombia Research Group in Health Economics University of Cartagena Cartagena Colombia Department of Biomedical Science University of Cape Coast Cape Coast Ghana Cardiology Department Ca

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM_2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM_2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM_2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM_2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM_2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am

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Accelerating internet penetration to rural areas: A government-sponsored internet-kiosks deployment project in Garut Regency, West Java of Indonesia

Accelerating internet penetration to rural areas: A governme...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： A. Kurniawan I. Zakia E. Wartika A.G. Austin School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Study Program of Film and Television Institut Seni Budaya Bandung Bandung Indonesia Faculty of Civil Engineering and Environment Institut Teknologi Bandung Bandung Indonesia

Internet penetration in developing countries depend on a variety of factors, including the Gross Domestic Product (GDP), the density of telephone connections, and the density of personal computer users. Internet kiosks have been deployed in 21 rural ditrict areas of Garut Regency to facilitate internet access for local/district government as well as for the community who have no access to internet Each district was equiped with 10 PCs, a printer, a scanner, and an internet connection either using DSL or cellular access technology. The program was government sponsored through the Ministry of Communications and information of the Republic of Indonesia. This program was also designed to provide education and training for the district internet kiosks operator as well as for the staffs of information technology at Garut Regency, on understanding, efficient use, management, maintenance, as well as the ethical/professional use of information to upgrade their skills. This study was then conducted to evaluate factors affecting internet penetration in rural areas of Garut Regency, West Java of Indonesia.

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Coverage and capacity trade-off using admission and power controlled CDMA system for wireless internet services in rural environments

Coverage and capacity trade-off using admission and power co...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

In this paper the coverage and capacity of CDMA system is evaluated using admission and power control to serve for low to medium speed internet services, such as digital TV or film/video streaming in rural areas. One of the unique characteristics of CDMA system is that it is possible to trade off between capacity and its coverage, called the cell-breathing. Open loop and closed loop power control can be used to increase the capacity of CDMA system; while admission control can be applied to trade-off between its capacity and the coverage. Computer simulation was conducted to evaluate the power control performance in Rayleigh fading channel. Then semi-analytical evaluation was performed to obtain the coverage-capacity trade-off. The result shows that the capacity of CDMA systems increases when power control was employed. Numerical and semi analytical evaluation show that CDMA coverage and capacity can be traded-off to meet various demand of traffic capacity and cell coverage in rural environments.

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Erratum to: Measurement of differential cross sections and W+/W− cross-section ratios for W boson production in association with jets at = 8 TeV with the ATLAS detector

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Journal of High Energy Physics 2020年第10期2020卷 1-20页

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Afik, Y. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Alberghi, G. L. Albert, J. Albicocco, P. Alconada Verzini, M. J. Alderweireldt, S. C. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A. V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D. J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Araujo Ferraz, V. Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baas, A. E. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Bakker, P. J. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Bandyopadhyay, A. Banerjee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barkeloo, J. T. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska-Blenessy, Z. Baroncelli, A. Bar Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States of America Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz United States of America Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene United States of America Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas — LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston United States of America Joint Institute for Nuclear Research JINR Dubna Dubna Russia IN

Two additions impacting tables 3 and 4 in ref. [1] are presented in the following. No significant impact is found for other results or figures in ref. [1].

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Heart sound feature extraction and classification using autoregressive power spectral density (AR-PSD) and statistics features

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AIP Conference Proceedings 2016年第1期1755卷

作者： Domy Kristomo Risanuri Hidayat Indah Soesanti Adi Kusjani 1Department of Electrical Engineering and Information Technology Faculty of Engineering Gadjah Mada University Jalan Grafika No. 2 Yogyakarta 55281 Indonesia 2Study Program of Computer Engineering STMIK AKAKOM of Yogyakarta Jalan Raya Janti 143 Karang Jambe Yogyakarta 55198 Indonesia

Heart auscultation is a screening method done by listening using a stethoscope for early diagnosis of heart disease, it is low cost and non-invasive, but it has a limitation of human hearing. This paper presents a noise-robust feature extraction method by combining and selecting a heart sound (HS) feature in time and frequency domain. Wavelet decomposition (WD) is used for noise removal. Features are extracted by AR-PSD and used as inputs for classification. The nine types of abnormal HS that were taken from Michigan Heart Sound Database were classified into nine categories. In this research, statistics features in time and frequency domain are used as additional features. Correlation-based Feature Selection (CFS) is used to select the best feature among 13 features extracted. The performance of a new feature set is called Feature Set 3 compared to CFS. The result shows that the proposed feature set achieves the highest level of accuracy.

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Proceedings from the IV Brazilian Meeting on Research Integrity, Science and Publication Ethics (IV BRISPE)

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Research Integrity and Peer Review 2017年第1期2卷 1-12页

作者： Sonia Vasconcelos Edson Watanabe L. P. Garcia E. Duarte M. C. Cassimiro M. M. P. Diós-Borges A. M. M. Soares C. H. Debenedito Silva A. A. P. Santa Rosa G. A. Fófano H. S. Pinheiro A. M. Gollner C. C. Santos S. M. R. Vasconcelos D. C. Machado P. V. S. Souza R. T. Souza M. D Ribeiro P. Biancovilli M. Fontes-Domingues V. C. Garbocci R. Neves M. D. Ribeiro R. Amaral M. M. M. Machado P. M. Lourenço V. Ronchi A. C. Furnival L. S. Gracioso M. D. P. Silva F. M. Litto M. Patrão Neves A. S. Carvalho J. Araújo S. Liskauskas R. Kant de Lima S. C. Bourguignon F. R. Mota H. G. Falcão J. C. Amaral A. C. Quintela A. Schtscherbyna A. Palma C. A. Guimarães D. Foguel E. H. Watanabe R. M. V. R. Almeida J. R. Lapa e Silva M. M. Sorenson B. C. Machado A. P. Vicentini A. A. B. Almodóvar R. M. Catarino H. H. Caiaffa Filho E. Damasio J. Leta L. V. R. Rezende S. Cruz-Riascos A. Abreu M. Russo P. G. Camacho M. Palácios N. R. A. Silva M. R. C. G. Novaes D. Guilhem H. S Selistre-de-Araujo A. S. C. Abreu Science Education Program Institute of Medical Biochemistry Leopoldo de Meis (IBqM) Federal University of Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Committee on Research Integrity (CRI) Advisory Council for Research Ethics (CTEP) Federal University of Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Electrical Engineering Program (PEE) Institute Alberto Luiz Coimbra of Graduate Studies and Research in Engineering (COPPE) Federal University of Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Institute for Applied Economic Research (IPEA) Brasília Federal District Brazil Secretary for Health Surveillance Ministry of Health Brasília Federal District Brazil Scientific Integrity Committee Oswaldo Cruz Foundation Oswaldo Cruz Institute (IOC/FIOCRUZ) Rio de Janeiro Brazil Scientific Integrity Committee Oswaldo Cruz Institute Oswaldo Cruz Foundation (IOC/FIOCRUZ) Rio de Janeiro Brazil Bioethics Institute Catholic University of Portugal Porto Portugal Rio de Janeiro State University (UERJ) Rio de Janeiro Brazil National Cancer Institute (INCA) Cancer Hospital IV - Ethics Committee for Clinical Research Rio de Janeiro Brazil Federal General Hospital of Bonsucesso Rio de Janeiro Brazil Human Research Ethics Committee University Hospital of Juiz de Fora (HU-UJFJ) Juiz de Fora Minas Gerais Brazil Faculty of Southeastern Minas Gerais (FACSUM) Juiz de Fora Minas Gerais Brazil São Pedro Educational Institute (IESPe) Juiz de Fora Minas Gerais Brazil University Hospital of Juiz de Fora (HU-UJFJ) Juiz de Fora Minas Gerais Brazil Department of Biology and Sciences Pedro II School Rio de Janeiro Brazil Science Education Program Institute of Medical Biochemistry Leopoldo de Meis Federal University of Rio de Janeiro (IBqM/UFRJ) Rio de Janeiro Brazil Professional Masters Program in Science Education Institute of Medical Biochemistry Leopoldo de Meis (IBqM) Federal University of Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Research Ethics Committee Clementino Fraga Filho University Hos

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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