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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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MOS-only M-2M DAC for ultra-low voltage applications

MOS-only M-2M DAC for ultra-low voltage applications

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Israel Sperotto Hamilton Klimach Sergio Bampi Microelectronics Graduate Program Federal University of Rio Grande do Sul Porto Alegre RS Brazil Electrical Engineering Department Federal University of Rio Grande do Sul Porto Alegre RS Brazil Informatics Institute Federal University of Rio Grande do Sul Porto Alegre RS Brazil

This work presents a study of the CMOS based R-2R ladder network (also called M-2M) Digital-to-Analog Converter (DAC) as a potential candidate for ultra-low voltage (ULV) applications, i.e. supply voltages VDD lower than 200mV. MOS transistors operate in subthreshold under such very low VDD, and the circuit analysis must be done using an all-region continuous MOSFET model. Simulation results in a commercial 130 nm process corroborate the presented analysis, showing that it is possible to implement this DAC topology for 6 to 8 bits operating under supply voltages from 70 mV to 140 mV.

关键词： MOSFET Semiconductor device modeling Analytical models Mathematical model CMOS integrated circuits Integrated circuit modeling

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Author Correction: Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk

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Nature genetics 2020年第3期52卷 354页

作者： Iris E Jansen Jeanne E Savage Kyoko Watanabe Julien Bryois Dylan M Williams Stacy Steinberg Julia Sealock Ida K Karlsson Sara Hägg Lavinia Athanasiu Nicola Voyle Petroula Proitsi Aree Witoelar Sven Stringer Dag Aarsland Ina S Almdahl Fred Andersen Sverre Bergh Francesco Bettella Sigurbjorn Bjornsson Anne Brækhus Geir Bråthen Christiaan de Leeuw Rahul S Desikan Srdjan Djurovic Logan Dumitrescu Tormod Fladby Timothy J Hohman Palmi V Jonsson Steven J Kiddle Arvid Rongve Ingvild Saltvedt Sigrid B Sando Geir Selbæk Maryam Shoai Nathan G Skene Jon Snaedal Eystein Stordal Ingun D Ulstein Yunpeng Wang Linda R White John Hardy Jens Hjerling-Leffler Patrick F Sullivan Wiesje M van der Flier Richard Dobson Lea K Davis Hreinn Stefansson Kari Stefansson Nancy L Pedersen Stephan Ripke Ole A Andreassen Danielle Posthuma Department of Complex Trait Genetics Center for Neurogenomics and Cognitive Research Amsterdam Neuroscience VU University Amsterdam the Netherlands. Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam the Netherlands. Department of Medical Epidemiology and Biostatistics Karolinska Institutet Stockholm Sweden. deCODE Genetics/ Amgen Reykjavik Iceland. Interdisciplinary Graduate Program Vanderbilt University Nashville TN USA. Institute of Gerontology and Aging Research Network-Jönköping (ARN-J) School of Health and Welfare Jönköping University Jönköping Sweden. NORMENT K.G. Jebsen Centre for Psychosis Research Institute of Clinical Medicine University of Oslo Oslo Norway. Division of Mental Health and Addiction Oslo University Hospital Oslo Norway. Institute of Psychiatry Psychology and Neuroscience King's College London London UK. Institute of Clinical Medicine University of Oslo Oslo Norway. Center for Age-Related Diseases Stavanger University Hospital Stavanger Norway. Department of Neurology Akershus University Hospital Lørenskog Norway. AHUS Campus University of Oslo Oslo Norway. Department of Psychiatry of Old Age Oslo University Hospital Oslo Norway. Department of Community Medicine University of Tromsø Tromsø Norway. Norwegian National Advisory Unit on Ageing and Health Vestfold Hospital Trust Tønsberg Norway. Centre for Old Age Psychiatry Research Innlandet Hospital Trust Ottestad Norway. Department of Geriatric Medicine Landspitali University Hospital Reykjavik Iceland. Geriatric Department Oslo University Hospital Oslo Norway. Department of Neuromedicine and Movement Science Norwegian University of Science and Technology Trondheim Norway. Department of Neurology St Olav's Hospital Trondheim University Hospital Trondheim Norway. Neuroradiology Section Department of Radiology and Biomedical Imaging University of California San Francisco CA USA. Department

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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Unintended pregnancy: a framework for prevention and options for midlife women in the US

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Women's midlife health 2017年第1期3卷 8页

作者： Versie Johnson-Mallard Elizabeth A Kostas-Polston Nancy Fugate Woods Katherine E Simmonds Ivy M Alexander Diana Taylor 1Department of Family Community and Health System Science Robert Wood Johnson Nurse Faculty Scholar Alum University of Florida College of Nursing Gainesville FL USA. 2Daniel K. Inouye Graduate School of Nursing Uniformed Services University of the Health Sciences Bethesda MD USA. 3Biobehavioral Nursing and Health Informatics Interim Associate Dean for Diversity Equity and Inclusion University of Washington School of Nursing Seattle WA USA. 4MGH Institute of Health Professions Boston MA USA. Director of Advance Practice Programs Storrs CT USA. 6UCSF School of Nursing Research Faculty Advancing New Standards in Reproductive Health Program (ANSIRH) UCSF Bixby Center for Global Reproductive Health University of California San Francisco CA USA.

Recently unintended pregnancies have been described as "a new kind of mid-life crisis." Given the high prevalence of unwanted or mistimed pregnancy in the US, we examined the sexual and reproductive health patterns of sexually active midlife women. An examination of the prevalence of unintended pregnancy among midlife women revealed a gap in data indicating unmet sexual and reproductive health needs of midlife women. The application of a framework for primary, secondary and tertiary prevention for unintended pregnancy may assist with guiding care for women and identifying implications for reproductive health policy and potential political interference as they relate to sexual and reproductive health in midlife women.

关键词： Abortion Age Contraception Framework Menopause Pregnancy Reproductive health Sex Transition Women

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Social support and user engagement in online health communities 18

Social support and user engagement in online health communit...

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18th Pacific Asia Conference on Information Systems, PACIS 2014

作者： Wang, Xi Zhao, Kang Interdisciplinary Graduate Program in Informatics University of Iowa Iowa CityIA United States Tippie College of Business University of Iowa Iowa CityIA United States

Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with those who face similar problems and are involved in different types of social supports, such as information support, emotional support and companionship. Using a case study of an OHC among breast cancer survivors, we first use machine learning techniques to reveal the types of social support embedded in each post from an OHC. Then we generate each user's contribution profile by aggregating the user's involvement in different types of social support and reveal the role the user plays in an OHC. By comparing online activities for users with different roles, we illustrate that users' involvement in various types of social support is related to their level of engagement in an OHC.

关键词： Health

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A sound-based online method for estimating the time-varying posture of a hose-shaped robot 12

A sound-based online method for estimating the time-varying ...

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12th IEEE International Symposium on Safety, Security and Rescue Robotics, SSRR 2014

作者： Bando, Yoshiaki Itoyama, Katsutoshi Konyo, Masashi Tadokoro, Satoshi Nakadai, Kazuhiro Yoshii, Kazuyoshi Okuno, Hiroshi G. Graduate School of Informatics Kyoto Univ. Kyoto606-8501 Japan Graduate School of Information Science Tohoku Univ. Miyagi980-8579 Japan Honda Research Institute Japan Co. Ltd. Saitama351-0114 Japan Graduate Program for Embodiment Informatics Waseda Univ. Tokyo169-0072 Japan

ISBN: (纸本)9781479941995

This paper presents an online method that can accurately estimate the time-varying posture of a moving hose-shaped robot having multiple microphones and loudspeakers. Sound-based posture estimation has been considered to be promising for circumventing the cumulative error problem of conventional integral-type methods using differential information obtained by inertial sensors. Our robot emits a reference signal from a loud-speaker one by one and estimates its posture by measuring the time differences of arrival (TDOAs) at the microphones. To accurately estimate the posture of the robot (the relative positions of the microphones and loudspeakers) even when the robot moves, we propose a novel state-space model that represents the dynamics of not only the posture itself but also its change rate in the state space. This model is used for predicting the current posture by using an unscented Kalman filter. The experiments using a 3m moving hose-shaped robot with eight microphones and seven loudspeakers showed that our method achieved less than 20 cm error at the tip position even after the robot moved over a long time, whereas the estimation error obtained by a conventional integral-type method increased monotonically over time. © 2014 IEEE.

关键词： Microphones

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Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies (vol 391, pg 1513, 2018)

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LANCET 2018年第10136期391卷 2212-2212页

作者： Wood, A. M. Kaptoge, S. Butterworth, A. S. [a]Department of Public Health and Primary Care University of Cambridge Cambridge UK [b]Medical University Innsbruck Innsbruck Austria [c]National Centre for Epidemiology and Population Health Australian National University Canberra Australia [d]MRC Biostatistics Unit Cambridge Institute of Public Health University of Cambridge Cambridge UK [e]NIHR BRC Nutritional Biomarker Laboratory University of Cambridge Cambridge UK [f]Norwegian Institute of Public Health Oslo Norway [g]National Institute for Public Health and the Environment Bilthoven Netherlands [h]Julius Centre for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands [i]Chiba Prefectural Institute of Public Health Chiba Japan [j]Department of Community Medicine University of Tromsø Tromsø Norway [k]Nuffield Department of Population Health Medical Sciences Division University of Oxford Oxford UK [l]The George Institute for Global Health University of Sydney Sydney NSW Australia [m]Bloomberg School of Public Health Johns Hopkins University Baltimore MD USA [n]School of Medicine Johns Hopkins University Baltimore MD USA [o]THL-National Institute for Health and Welfare Helsinki Finland [p]Copenhagen University Hospital Copenhagen Denmark [q]Department of Clinical Medicine University of Copenhagen Copenhagen Denmark [r]School of Medicine University of Western Australia Perth WA Australia [s]Fiona Stanley Hospital Perth WA Australia [t]Harry Perkins Institute of Medical Research Perth WA Australia [u]London School of Hygiene & Tropical Medicine London UK [v]Department of Clinical Sciences Malmö Lund University Malmö Sweden [w]Graduate School of Public Health University of Pittsburgh Pittsburgh PA USA [x]CESP INSERM UMRS 1018 Villejuif Cedex France [y]Department of Epidemiology and Public Health University College London London UK [z]92 Deutsches Herzzentrum München Technische Universität München Munich Germany DZHK (German Centre for Cardiovascular R

Summary Background Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular *** We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th-95th percentile 1·04-13·5]) from 71 011 participants from 37 *** In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk arou

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A robot quizmaster that can localize, separate, and recognize simultaneous utterances for a fastest-voice-first quiz game

A robot quizmaster that can localize, separate, and recogniz...

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IEEE-RAS International Conference on Humanoid Robots

作者： Izaya Nishimuta Naoki Hirayama Kazuyoshi Yoshii Katsutoshi Itoyama Hiroshi G. Okuno Graduate School of Informatics Kyoto University Sakyo-ku Kyoto Japan Graduate Program for Embodiment Informatics Waseda University Tokyo Japan

This paper presents an interactive humanoid robot that can moderate a multi-player fastest-voice-first-type quiz game by leveraging state-of-the-art robot audition techniques such as sound source localization and separation and speech recognition. In this game, a player who says "Yes" first gets a right to answer a question, and players are allowed to barge in a questionary utterance of the quizmaster. The robot needs to identify which player says "Yes" first, even if multiple players respond at almost exactly the same time, and must judge the correctness of the answer given by the player. To enable natural human-robot interaction, we believe that the robot should use its own microphones (i.e., ears) embedded in the head, rather than having pin microphones attached to individual players. In this paper we use a robot audition system called HARK for separating the mixture of audio signals recorded by the ears into multiple source signals (i.e., almost the simultaneous utterances of "Yes" and the questionary utterance) and estimating the direction of each source. To judge the correctness of an answer, we use a speech recognizer called Julius. Experimental results showed that our robot can correctly identify which player spoke first when the players' utterances differed by 60 msec.

关键词： Robots Games Speech recognition Noise Speech Loudspeakers Microphones

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A second update on mapping the human genetic architecture of COVID-19

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Nature 2023年第7977期621卷 E7-E26页

作者： Masahiro Kanai Christine Stevens Benjamin M. Neale Mark Daly Andrea Ganna Amy Trankiem Mary K. Balaconis Samuli Ripatti Lindo Nkambul Mark J. Daly Sam Bryant Matthew Solomonson Shea J. Andrews Mattia Cordioli Juha Karjalainen Juha Mehtonen Matti Pirinen Andrea Corbetta Bradley Jermy Kati Donner Katja Kivinen Aarno Palotie Mari Kaunisto Kumar Veerapen Konrad J. Karczewski Alicia R. Martin Elizabeth G. Atkinson Kristin Tsuo Nikolas Baya Rahul Gupta Raymond K. Walters Duncan S. Palmer Gopal Sarma Nathan Cheng Wenhan Lu Claire Churchhouse Jacqueline I. Goldstein Daniel King Wei Zhou Cotton Seed Hilary Finucane F. Kyle Satterstrom Gita A. Pathak Akiko Iwasaki Karolina Chwialkowska Karolina Chwiałkowska Brooke N. Wolford Hajar Fauzan Ahmad Shea Andrews Kathrin Aprile von Hohenstaufen Puoti Palwende R. Boua Guillaume Butler-Laporte Celia M. T. Greenwood Bartha M. Knoppers Mark Lathrop Carmen L. Cadilla Francesca Colombo Nicole Dueker Chloe Kirk Atanu Kumar Dutta Yasser M. El-Sherbiny Jehan J. El-Jawhari Doaa Shahin Ahmed Elzeiny Tamer A. Mansour Madonna M. Eltoukhy Attia A. S. Mohamed Sahar Esmaeeli Annika Faucon Israel Fernández Cadenas Israel Fernandez-Cadenas Laia Llucià-Carol Natalia Cullell Elena Muiño Jara Cárcel-Márquez Margherita Francescatto Laurent Francioli Lindokuhle Nkambule Jatin Arora Soumya Raychaudhuri Caroline Cusick Lude Franke Macarena Fuentes Macarena Fuentes-Guajardo David Gómez Cabrero Emi N. Harry Philip Jansen József L. Szentpéteri Réka Várnai Elżbieta Kaja Athanasios Kousathanas Dorote Pasko Mark J. Caulfield Alex Stuckey Christopher A. Odhams Susan Walker Daniel Rhodes Richard H. Scott Loukas Moutsianas Afshan Siddiq Peter Goddard Sally Donovan Tala Zainy Fiona Maleady-Crowe Linda Todd Shahla Salehi Greg Elgar Georgia Chan Prabhu Arumugam Christine Patch Augusto Rendon Tom A. Fowler Jose E. Krieger Sanjay K. Patel Audrey Lemaçon Sophie Limou Pietro Lió Eirini Marouli Charles Hinds Minttu M. Marttila Carolina Medina-Gómez Isabelle Migeotte Soumyajit Mondal Andrés Moreno-Estrada Leire Moya Tomok Broad Institute of MIT and Harvard Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland Public Health Faculty of Medicine University of Helsinki Helsinki Finland Analytic & Translational Genetics Unit Massachusetts General Hospital Boston MA USA Stanley Center for Psychiatric Research & Program in Medical and Population Genetics Cambridge UK Institute for Molecular Medicine Finland (FIMM) Univerisity of Helsinki Helsinki Finland University of California San Francisco San Francisco CA USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Department of Psychiatry School of Medicine Yale University New Haven CT USA Veteran Affairs Connecticut Healthcare System West Haven CT USA Yale University New Haven CT USA Centre for Bioinformatics and Data Analysis Medical University of Bialystok Bialystok Poland Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA Faculty of Industrial Sciences and Technology Universiti Malaysia Pahang Pahang Malaysia Icahn School of Medicine at Mount Sinai New York NY USA Genolier Innovation Network and Hub Swiss Medical Network Genolier Healthcare Campus Genolier Switzerland Immediate Independent Multidisciplinary Med & Biotech Research Association Milan Italy Clinical Research Unit of Nanor

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Development of a robot quizmaster with auditory functions for speech-based multiparty interaction

Development of a robot quizmaster with auditory functions fo...

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IEEE/SICE International Symposium on System Integration

作者： Izaya Nishimuta Kazuyoshi Yoshii Katsutoshi Itoyama Hiroshi G. Okuno Graduate School of Informatics Kyoto University Sakyo-ku Kyoto Japan Graduate Program for Embodiment Informatics Waseda University Shinjuku Tokyo Japan

This paper presents a robot quizmaster that has auditory functions (i.e., ears) for moderating a multiplayer quiz game. The most basic form of oral interaction in a quiz game is that a quizmaster reads aloud a question, and each player is allowed to answer it whenever the answer comes to his or her mind. A critical problem in such oral interaction is that if multiple players speak almost simultaneously for answering, it is difficult for a “human” quizmaster to recognize overlapping answers and judge the correctness of each answer. To avoid this problem, players have conventionally been required to push a button, raise a hand, or say “Yes” to just get a right to answer a question before doing it. This requirement, however, inhibits natural oral interaction. In this paper we propose a “robot” quizmaster that can identify a player who correctly answers a question first, even when multiple players utter answers almost at the same time. Since our robot uses its own microphones (ears) embedded in the head, individual players are not required to wear small pin microphones close to their mouths. To localize, separate, and recognize overlapping utterances captured by the ears, we use a robot audition software called HARK and an automatic speech recognizer called Julius. Experimental results showed the effectiveness of our approach.

关键词： Robots Games Speech recognition Speech Noise Microphones Ear

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