检索结果-内蒙古大学图书馆

Between Access and Privacy: Challenges in Sharing Health Data

Yearbook of medical informatics 2018年第1期27卷 55-59页

作者： Malin, Bradley Goodman, Kenneth Department of Biomedical Informatics Vanderbilt University Nashville TN United States Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN United States Institute for Bioethics and Health Policy University of Miami Miami FL United States

OBJECTIVE: To summarize notable research contributions published in 2017 on data sharing and privacy issues in medical informatics.;METHODS: An extensive search of PubMed/Medline, Web of Science, ACM Digital Library, IEEE Xplore, and AAAI Digital Library was conducted to uncover the scientific contributions published in 2017 that addressed issues of biomedical data sharing, with a focus on data access and privacy. The selection process was based on three steps: (i) a selection of candidate best papers, (ii) the review of the candidate best papers by a team of international experts with respect to six predefined criteria, and (iii) the selection of the best papers by the editorial board of the Yearbook Results: Five best papers were selected. They cover the lifecycle of biomedical data collection, use, and sharing. The papers introduce 1) consenting strategies for emerging environments, 2) software for searching and retrieving datasets in organizationally distributed environments, 3) approaches to measure the privacy risks of sharing new data increasingly utilized in research and the clinical setting (e.g., genomic), 4) new cryptographic techniques for querying clinical data for cohort discovery, and 5) novel game theoretic strategies for publishing summary information about genome-phenome studies that balance the utility of the data with potential privacy risks to the participants of such studies.;CONCLUSION: The papers illustrated that there is no one-size-fitsall solution to privacy while working with biomedical data. At the same time, the papers show that there are opportunities for leveraging newly emerging technologies to enable data use while minimizing privacy risks. Georg Thieme Verlag KG Stuttgart.

关键词： Health records genomics data sharing privacy security

来源：评论

学校读者我要写书评

暂无评论

Non-invasive wearable system for Hypoglycemia detection: A proof of concept user-centered design process 62

Non-invasive wearable system for Hypoglycemia detection: A p...

引用

62nd Human Factors and Ergonomics Society Annual Meeting, HFES 2018

作者： Zhu, Yibo Zahed, Karim Mehta, Ranjana K. Sasangohar, Farzan Erraguntla, Madhav Lawley, Mark Abbas, Hasan Tahir Qaraqe, Khaled School of Public Health Department of Environmental and Occupational Safety Texas A and M University College StationTX United States Department of Industrial and Systems Engineering Texas A and M University College StationTX United States Department of Electrical and Computer Engineering Texas A and M University Qatar Doha Qatar

ISBN: (纸本)9781510889538

About 425 million adults around the world were living with diabetes in 2017. A relevant condition called Hypoglycemia is characterized by a dangerous low level of blood sugar that could be fatal to diabetic patients. Continuous glucose monitoring systems (CGMS) are the most popular commercially available technology for detecting diabetic hypoglycemia. However, CGMSs are invasive, costly, and not user-centric thereby not sustainable for diabetes management. This paper documents our initial efforts in designing an inexpensive, non-invasive, wearable physiological tremor sensory system to detect the onset of hypoglycemic events of diabetic patients. The design cycle briefly presented here includes: 1) determination of system (technology and user) requirements, 2) development of the tremor detection prototype, and 3) testing and validation of the system in non-clinical and clinical settings using human factors, data analytics, and biomedical sciences techniques and approaches. © 2018 Human Factors an Ergonomics Society Inc.. All rights reserved.

关键词： Insulin

来源：评论

学校读者我要写书评

暂无评论

Automated Abdominal Aortic Calcification Assessment and Major Adverse Cardiovascular Events in People Undergoing Osteoporosis Screening

引用

Heart, Lung and Circulation 2024年 33卷 S394-S395页

作者： C. Smith M. Sim Z. Illyas S. Gilani D. Suter S. Reid B. Monchka M. Jafari Jozani G. Figtree J. Schousboe W. Leslie J. Lewis Nutrition & Health Innovation Research Institute Edith Cowan University Perth WA Australia Medical School University of Western Australia Perth WA Australia Centre for AI&ML School of Science Edith Cowan University Perth WA Australia Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada George and Fay Yee Centre for Healthcare Innovation University of Manitoba Winnipeg MB Canada Department of Statistics University of Manitoba Winnipeg MB Canada Faculty of Health and Medicine The University of Sydney Sydney NSW Australia Kolling Institute of Medical Research St Leonards NSW Australia Park Nicollet Clinic and HealthPartners Institute HealthPartners Minneapolis MN USA Division of Health Policy and Management University of Minnesota Minneapolis MN USA Departments of Medicine and Radiology University of Manitoba Winnipeg MB Canada Centre for Kidney Research Children's Hospital at Westmead School of Public Health Sydney Medical School The University of Sydney Sydney NSW Australia

来源：评论

学校读者我要写书评

暂无评论

European advances in digital rheumatology: explainable insights and personalized digital health tools for psoriatic arthritis

引用

eClinicalMedicine 2025年 84卷 103243-103243页

作者： Hadjileontiadis, Leontios J. Charisis, Vasileios Hadjidimitriou, Stelios Dias, Sofia B. Apostolidis, George Dimaridis, Giannis Kitsas, Ilias Karlas, Angelos Fasoula, Nikolina-Alexia Levi-Schaffer, Francesca Silva, Hugo Dimitroulas, Theodoros Rodrigues, Ana Maria Coates, Laura C. Luime, Jolanda Tchetverikov, Ilja Department of Biomedical Engineering & Biotechnology College of Medicine and Life Sciences Khalifa University of Science and Technology Abu Dhabi United Arab Emirates Department of Electrical & Computer Engineering College of Engineering Aristotle University of Thessaloniki Thessaloniki Greece Centro Interdisciplinar de Performance Humana (CIPER) Faculdade de Motricidade Humana Universidade de Lisboa Lisbon Portugal Clinic and Polyclinic for Vascular and Endovascular Surgery TUM University Hospital Hospital Rechts der Isar Technical University of Munich Munich Germany Chair for Computer Aided Medical Procedures & Augmented Reality Technical University of Munich Munich Germany DZHK (German Centre for Cardiovascular Research) Partner Site Munich Heart Alliance Munich Germany Institute for Drug Research School of Pharmacy Faculty of Medicine The Hebrew University of Jerusalem Jerusalem Israel Instituto de Telecomunicações (IT) Instituto Superior Técnico (IST) Universidade de Lisboa Lisbon Portugal PLUX Biosignals Lisbon Portugal 4th Department of Internal Medicine School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Comprehensive Health Research Centre (CHRC) Nova Medical School and Rheumatology Faculdade de Ciências Médicas Universidade de Lisboa Lisbon Portugal Sociedade Portuguesa De Reumatologia Portugal Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford United Kingdom Department of Public Health Erasmus MC University Medical Center Rotterdam Netherlands Department of Rheumatology Albert Schweitzer Hospital Dordrecht Netherlands Stichting Cicero-Collectief Initiatief Voor Creatief En Educatief Reuma Onderzoek Netherlands

The shift from traditional to technology-based diagnosis and management of psoriatic arthritis (PsA) represents a significant evolution in patient care. Traditionally, PsA was diagnosed and managed through clinical evaluations, physical examinations, and basic imaging techniques. With the evolution of digital technologies, the PsA care is transforming, giving rise to the field of digital rheumatology. In this vein, Europe has invested in research initiatives, like iPROLEPSIS, that could accelerate this transformation and redefine PsA care within a digital world. In this Viewpoint we present the current clinical PsA landscape, highlight the PsA patients' interaction with the digital world, and showcase the novel iPROLEPSIS digital offerings. The latter scaffold digital rheumatology by identifying PsA key drivers. Moreover, they support personalized PsA risk prediction and improve early PsA detection. Furthermore, they enable precise PsA treatment strategies and digital therapeutics within a novel digital health ecosystem. © 2025 The Author(s)

关键词： Digital rheumatology Digital therapeutics Explainable AI models iPROLEPSIS European research initiative Novel digital biomarkers Psoriatic arthritis

来源：评论

学校读者我要写书评

暂无评论

SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver

arXiv

引用

arXiv 2019年

作者： Wang, Po-Wei Donti, Priya L. Wilder, Bryan Kolter, Zico School of Computer Science Carnegie Mellon University PittsburghPA United States Department of Engineering & Public Policy Carnegie Mellon University PittsburghPA United States Department of Computer Science University of Southern California Los AngelesCA United States Bosch Center for Artificial Intelligence PittsburghPA United States

Integrating logical reasoning within deep learning architectures has been a major goal of modern AI systems. In this paper, we propose a new direction toward this goal by introducing a differentiable (smoothed) maximum satisfiability (MAXSAT) solver that can be integrated into the loop of larger deep learning systems. Our (approximate) solver is based upon a fast coordinate descent approach to solving the semidefinite program (SDP) associated with the MAXSAT problem. We show how to analytically differentiate through the solution to this SDP and efficiently solve the associated backward pass. We demonstrate that by integrating this solver into end-to-end learning systems, we can learn the logical structure of challenging problems in a minimally supervised fashion. In particular, we show that we can learn the parity function using single-bit supervision (a traditionally hard task for deep networks) and learn how to play 9×9 Sudoku solely from examples. We also solve a "visual Sudoku" problem that maps images of Sudoku puzzles to their associated logical solutions by combining our MAXSAT solver with a traditional convolutional architecture. Our approach thus shows promise in integrating logical structures within deep learning. Copyright © 2019, The Authors. All rights reserved.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Operating System Security Management and Ease of Implementation (Passwords, Firewalls and Antivirus) 15th

Operating System Security Management and Ease of Implementat...

引用

15th International Conference on Information Technology : New Generations, ITNG 2018

作者： Zare, Hossein Olsen, Peter Zare, Mohammad Jalal Azadi, Mojgan University of Maryland University College Upper MarlboroMD United States Department of Health Policy and Management The Johns Hopkins Center for Disparities Solution The Johns Hopkins Bloomberg School of Public Health BaltimoreMD United States Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Catonsville BaltimoreMD United States Department of Computer Science and Engineering Azad University Yazd Iran The Johns Hopkins University BaltimoreMD United States

ISBN: (纸本)9783319770277

Recent widely-known hacking exploits have increased the focus on computer and network security. System users need systems to provide confidentiality, integrity, availability and authenticity for their data. Access control, firewalls, and antivirus software are three ways to provide system security. They address different aspects of computer security with complementary advantages and disadvantages. © 2018, Springer International Publishing AG, part of Springer Nature.

关键词： Personal computing

来源：评论

学校读者我要写书评

暂无评论

Machine learning used to study risk factors for chronic diseases: A scoping review

引用

Canadian journal of public health = Revue canadienne de sante publique 2025年 2025 Jun 11页

作者： Mahek Shergill Steve Durant Sharon Birdi Roxana Rabet Carolyn Ziegler Shehzad Ali David Buckeridge Marzyeh Ghassemi Jennifer Gibson Ava John-Baptiste Jillian Macklin Melissa McCradden Kwame McKenzie Parisa Naraei Akwasi Owusu-Bempah Laura C Rosella James Shaw Ross Upshur Sharmistha Mishra Andrew D Pinto Upstream Lab MAP Centre for Urban Health Solutions Li Ka Shing Knowledge Institute St. Michael's Hospital Toronto ON Canada. Michael G. DeGroote School of Medicine McMaster University Hamilton ON Canada. Health Science Library Unity Health Toronto Toronto ON Canada. Department of Epidemiology and Biostatistics Western Centre for Public Health & Family Medicine Western University London ON Canada. Department of Health Sciences University of York York UK. WHO Collaborating Centre for Knowledge Translation and Health Technology Assessment in Health Equity Ottawa ON Canada. Department of Epidemiology Biostatistics and Occupational Health School of Population and Global Health McGill University Montreal QC Canada. Department of Electrical Engineering and Computer Science (EECS) Institute for Medical Engineering & Science (IMES) MIT Cambridge MA USA. Joint Centre for Bioethics University of Toronto Toronto ON Canada. Departments of Epidemiology & Biostatistics Anesthesia & Perioperative Medicine Schulich Interfaculty Program in Public Health Western University London ON Canada. Undergraduate Medical Education Faculty of Medicine University of Toronto Toronto ON Canada. Department of Bioethics The Hospital for Sick Children Toronto ON Canada. Genetics & Genome Biology SickKids Research Institute Toronto ON Canada. Division of Clinical Public Health Dalla Lana School of Public Health University of Toronto Toronto ON Canada. Wellesley Institute Toronto ON Canada. CAMH Toronto ON Canada. Department of Computer Science Toronto Metropolitan University Toronto ON Canada. Department of Sociology Faculty of Arts & Sciences University of Toronto Toronto ON Canada. Institute for Better Health Trillium Health Partners Toronto ON Canada. Department of Physical Therapy Faculty of Medicine University of Toronto Toronto ON Canada. Department of Family and Community Medicine Faculty of Medicine University of Toronto Toronto ON Canada. Division

OBJECTIVES:Machine learning (ML) has received significant attention for its potential to process and learn from vast amounts of data. Our aim was to perform a scoping review to identify studies that used ML to study risk factors for chronic diseases at a population level, notably those that incorporated methods to mitigate algorithmic bias. We focused on ML applications for the most common risk factors for chronic disease: tobacco use, alcohol use, unhealthy eating, physical activity, and psychological stress. METHODS:We searched the peer-reviewed, indexed literature using Medline (Ovid), Embase (Ovid), Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews (Ovid), Scopus, ACM Digital Library, INSPEC, and Web of Science's Science Citation Index, Social Sciences Citation Index, and Emerging Sources Citation Index. Among the included studies, we examined whether bias was considered and identified strategies employed to mitigate bias. SYNTHESIS:The search identified 10,329 studies, and 20 met our inclusion criteria. The studies we identified used ML for a wide range of goals, from prediction of chronic disease development to automating the classification of data to identifying new associations between risk factors and disease. Nine studies (45%) included some discussion of algorithmic bias. Studies that incorporated a broad array of sociodemographic variables did so primarily to improve the performance of a ML model rather than to mitigate potential harms to populations made vulnerable by social and economic policies. CONCLUSION:This work contributes to our understanding of how ML can be used to advance population and public health.

关键词： Artificial intelligence Machine learning Non-communicable diseases Population health public health Risk factors

来源：评论

学校读者我要写书评

暂无评论

Online Self-learning for Smart HVAC Control

Online Self-learning for Smart HVAC Control

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Tzu-Yin Chao Manh-Hung Nguyen Ching-Chun Huang Chien-Cheng Liang Chen-Wu Chung Dept. of Electrical Engineering National Chung Cheng University Chiayi Taiwan Dept. of Computer Science National Chiao Tung University Hsinchu Taiwan Public Utilities Service Department Taiwan Semiconductor Manufacturing Company Ltd.

In this paper, we introduce an online-learning method to model the property of an office building. Unlike conventional control methods where the building property is modeled via a simulator or through offline learning, our building model is adaptively updated according to the dynamic response of a real environment. Upon the building model for environment prediction, the proposed action agent can control the heating, ventilation, and air conditioning (HVAC) system in a smarter way by scheduling the temperature reference point. To online learn the model and improve the agent, two practical and seldom discussed issues are addressed. The first challenge is data bias where the collected initial training dataset can only partially reveal the statistical mapping between the control input and the environment response. Hence, the trained model may lack generalization. To overcome the data bias issue, a data augmentation method is proposed to embed physical logic in order to train a proper initial model. Next, an online learning process is introduced to update the model generality during the system operation phase. The second practical issue is the constraints on agent exploration for discovering unknown data samples. During the business hours, to comfort employees, a control agent is not allowed to explore the possible controlling space randomly. To balance data collection and control stability, we introduce a hybrid control strategy that considers both the human control rule and the agent action. A confidence score of the agent model is also automatically estimated to determine a suitable control strategy finally. Our experiments have realized in an office building. The results outperform conventional methods and show its superior in terms of control stability.

关键词： Buildings HVAC Adaptation models Training Temperature control Data models Predictive models

来源：评论

学校读者我要写书评

暂无评论

Vaccinations or Non-Pharmaceutical Interventions: Safe Reopening of Schools in England

Research Square

引用

Research Square 2021年

作者： Cuesta-Lazaro, Carolina Quera-Bofarull, Arnau Aylett-Bullock, Joseph Lawrence, Bryan N. Fong, Kevin Icaza-Lizaola, Miguel Sedgewick, Aidan Truong, Henry Vernon, Ian Williams, Julian Pagel, Christina Krauss, Frank Institute for Data Science Durham University Durham United Kingdom Institute for Computational Cosmology Durham University Durham United Kingdom Institute for Particle Physics Phenomenology Durham University Durham United Kingdom National Centre for Atmospheric Science University of Reading Reading United Kingdom Departments of Meteorology and Computer Science University of Reading Reading United Kingdom Department of Science Technology Engineering and Public Policy University College London London United Kingdom Department of Anaesthesia University College London Hospital London United Kingdom Centre for Extragalactic Astronomy Durham University Durham United Kingdom Department of Mathematical Sciences Durham University DurhamDH1 3LE United Kingdom Institute for Hazard Risk & Resilience Durham University DurhamDH1 3LE United Kingdom Clinical Operational Research Unit University College London United Kingdom

With high levels of the Delta variant of COVID-19 circulating in England during September 2021, schools are set to reopen with few school-based non-pharmaceutical interventions (NPIs). In this paper, we present simulation results obtained from the individual-based model, JUNE, for English school opening after a prior vaccination campaign using an optimistic set of assumptions about vaccine efficacy and the likelihood of prior-reinfection. We take a scenario-based approach to modelling potential interventions to assess relative changes rather than real-world forecasts. Specifically, we assess the effects of vaccinating those aged 16-17, those aged 12-17, and not vaccinating children at all relative to only vaccinating the adult population, addressing what might have happened had the UK began teenage vaccinations earlier. Vaccinating children in the 12-15 age group would have had a significant impact on the course of the epidemic, saving thousands of lives overall in these simulations. In the absence of such a vaccination campaign our simulations show there could still be a significant positive impact on the epidemic (fewer cases, fewer deaths) by continuing NPI strategies in schools. Our analysis suggests that the best results in terms of lives saved are likely derived from a combination of the now planned vaccination campaign and NPIs in schools. © 2021, CC BY.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Joint Temporal Dietary and Physical Activity Patterns: Associations with Health Status Indicators and Chronic Diseases

引用

Current Developments in Nutrition 2020年第SUPPL 2期4卷 4140590-4140590页

作者： Lin, Luotao Aqeel, Marah Guo, Jiaqi Gelfand, Saul Delp, Edward Bhadra, Anindya Richards, Elizabeth Hennessy, Erin Eicher-Miller, Heather Department of Nutrition Science Purdue University School of Electrical and Computer Engineering Purdue University Department of Statistics Purdue University School of Nursing Purdue University Friedman School of Nutrition Science and Policy Tufts University

AbstractObjectivesThe aims of this study are to (1) create clusters of joint temporal patterns of diet and physical activity (PA), and (2) determine the association of these clusters with health status indicators including body mass index (BMI), waist circumference (WC), fasting plasma glucose, hemoglobin A1c, triglyceride, high-density lipoprotein cholesterol, total cholesterol, blood pressure and health outcomes including obesity, Type 2 Diabetes (T2DM) and metabolic syndrome (MS) in U.S. adults 20–65 years. MethodsA random day of PA from accelerometry data and the first day 24 hour dietary recall collected in the National Health and Nutrition Examination Survey 2003–2006 were used to determine absolute PA intensity, absolute energy intake, and the time of these activities. Dietary and PA data from 1,627 U.S. adults were Z-normalized. Dynamic time warping (DTW) coupled with kernel-k means clustering algorithm was used to develop joint temporal dietary and PA patterns that maximally partition individuals with similar temporal behaviors into mutually exclusive clusters derived from the data rather than predefined standards. Multivariate regression models adjusted for ptential confounders, multiple comparisons and survey design factors determined associations between joint temporal patterns and health status indicators along with health outcomes ( P < 0.05/6). ResultsSignificant differences of health status indicators and health outcomes were discovered among four clusters. A cluster, representing a joint temporal dietary and PA pattern with proportionally equivalent average energy consumed with two energy intake peaks at 1 PM and 8 PM and the lowest PA intensity compared to all other clusters, was associated with significantly higher BMI (β: 3.5, P < 0.0001), WC (β: 9.5, P < 0.0001), and significantly higher odds of obesity (Odds Ratio = 4.685, P < 0.0001) compared to a cluster with similar energy and intake peaks and the highest PA intensity compared to all other c

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：