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1.
Sensors (Basel) ; 22(5)2022 Feb 22.
Article in English | MEDLINE | ID: covidwho-1742603

ABSTRACT

The Internet of Things consists of "things" made up of small sensors and actuators capable of interacting with the environment. The combination of devices with sensor networks and Internet access enables the communication between the physical world and cyberspace, enabling the development of solutions to many real-world problems. However, most existing applications are dedicated to solving a specific problem using only private sensor networks, which limits the actual capacity of the Internet of Things. In addition, these applications are concerned with the quality of service offered by the sensor network or the correct analysis method that can lead to inaccurate or irrelevant conclusions, which can cause significant harm for decision makers. In this context, we propose two systematic methods to analyze spatially distributed data Internet of Things. We show with the results that geostatistics and spatial statistics are more appropriate than classical statistics to do this analysis.


Subject(s)
Internet of Things , Communication , Computer Communication Networks , Internet
2.
Stud Health Technol Inform ; 288: 122-133, 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1662547

ABSTRACT

From 1992 to 1995 Donald A.B. Lindberg M.D. served concurrently as the founding director of the National Coordination Office (NCO) for High Performance Computing and Communications (HPCC) and NLM director. The NCO and its successors coordinate the Presidential-level multi-agency HPCC research and development (R&D) program called for in the High-Performance Computing Act of 1991. All large Federal science and technology R&D and applications agencies, including those involved in medical research and health care, participate in the now-30-year-old program. Lindberg's HPCC efforts built on his pioneering work in developing and applying advances in computing and networking to meet the needs of the medical research and health care communities. As part of NLM's participation in HPCC, Lindberg promoted R&D and demonstrations in telemedicine, including testbeds, medical data privacy, medical decision-making, and health education. That telemedicine technologies were ready to meet demand during the COVID-19 pandemic is testament to Lindberg's visionary leadership.


Subject(s)
Computer Communication Networks , National Library of Medicine (U.S.) , Telemedicine , COVID-19 , Humans , Leadership , Medical Informatics , Pandemics , United States
3.
Big Data ; 10(1): 54-64, 2022 02.
Article in English | MEDLINE | ID: covidwho-1522089

ABSTRACT

The biosensors on a human body form a wireless body area network (WBAN) that can examine various physiological parameters, such as body temperature, electrooculography, electromyography, electroencephalography, and electrocardiography. Deep learning can use health information from the embedded sensors on the human body that can help monitoring diseases and medical disorders, including breathing issues and fever. In the context of communication, the links between the sensors are influenced by fading due to diffraction, reflection, shadowing by the body, clothes, body movement, and the surrounding environment. Hence, the channel between sensors and the central unit (CU), which collects data from sensors, is practically imperfect. Therefore, in this article, we propose a deep learning-based COVID-19 detection scheme using a WBAN setup in the presence of an imperfect channel between the sensors and the CU. Moreover, we also analyze the impact of correlation on WBAN by considering the imperfect channel. Our proposed algorithm shows promising results for real-time monitoring of COVID-19 patients.


Subject(s)
COVID-19 , Communicable Diseases , Computer Communication Networks , Humans , SARS-CoV-2 , Wireless Technology
4.
J Child Adolesc Psychopharmacol ; 31(7): 464-474, 2021 09.
Article in English | MEDLINE | ID: covidwho-1429159

ABSTRACT

Objectives: To describe the development of a protocol and practical tool for the safe delivery of telemental health (TMH) services to the home. The COVID-19 pandemic forced providers to rapidly transition their outpatient practices to home-based TMH (HB-TMH) without existing protocols or tools to guide them. This experience underscored the need for a standardized privacy and safety tool as HB-TMH is expected to continue as a resource during future crises as well as to become a component of the routine mental health care landscape. Methods: The authors represent a subset of the Child and Adolescent Psychiatry Telemental Health Consortium. They met weekly through videoconferencing to review published safety standards of care, existing TMH guidelines for clinic-based and home-based services, and their own institutional protocols. They agreed on three domains foundational to the delivery of HB-TMH: environmental safety, clinical safety, and disposition planning. Through multiple iterations, they agreed upon a final Privacy and Safety Protocol for HB-TMH. The protocol was then operationalized into the Privacy and Safety Assessment Tool (PSA Tool) based on two keystone medical safety constructs: the World Health Organization (WHO) Surgical Safety Checklist/Time-Out and the Checklist Manifesto. Results: The PSA Tool comprised four modules: (1) Screening for Safety for HB-TMH; (2) Assessment for Safety During the HB-TMH Initial Visit; (3) End of the Initial Visit and Disposition Planning; and (4) the TMH Time-Out and Reassessment during subsequent visits. A sample workflow guides implementation. Conclusions: The Privacy and Safety Protocol and PSA Tool aim to prepare providers for the private and safe delivery of HB-TMH. Its modular format can be adapted to each site's resources. Going forward, the PSA Tool should help to facilitate the integration of HB-TMH into the routine mental health care landscape.


Subject(s)
Adolescent Health Services/organization & administration , COVID-19 , Child Health Services/organization & administration , Clinical Protocols/standards , Home Care Services , Mental Health Services/organization & administration , Patient Safety , Privacy , Telemedicine , Adolescent , COVID-19/epidemiology , COVID-19/prevention & control , Child , Computer Communication Networks/standards , Delivery of Health Care/methods , Delivery of Health Care/organization & administration , Home Care Services/ethics , Home Care Services/standards , Home Care Services/trends , Humans , SARS-CoV-2 , Telemedicine/ethics , Telemedicine/methods , United States
5.
Sci Rep ; 11(1): 17332, 2021 08 30.
Article in English | MEDLINE | ID: covidwho-1379335

ABSTRACT

Private Set Intersection Cardinality that enable Multi-party to privately compute the cardinality of the set intersection without disclosing their own information. It is equivalent to a secure, distributed database query and has many practical applications in privacy preserving and data sharing. In this paper, we propose a novel quantum private set intersection cardinality based on Bloom filter, which can resist the quantum attack. It is a completely novel constructive protocol for computing the intersection cardinality by using Bloom filter. The protocol uses single photons, so it only need to do some simple single-photon operations and tests. Thus it is more likely to realize through the present technologies. The validity of the protocol is verified by comparing with other protocols. The protocol implements privacy protection without increasing the computational complexity and communication complexity, which are independent with data scale. Therefore, the protocol has a good prospects in dealing with big data, privacy-protection and information-sharing, such as the patient contact for COVID-19.


Subject(s)
COVID-19 , Computer Security , Confidentiality , Computer Communication Networks , Confidentiality/legislation & jurisprudence , Humans , Information Dissemination
7.
Antimicrob Resist Infect Control ; 10(1): 102, 2021 07 02.
Article in English | MEDLINE | ID: covidwho-1295486

ABSTRACT

INTRODUCTION: In late 2019, a novel coronavirus was detected in China. Supported by its respiratory transmissibility, even by people infected without symptomatic disease, this coronavirus soon began to rapidly spread worldwide. BACKGROUND: Many countries have implemented different infection control and containment strategies due to ongoing community transmission. In this context, contact tracing as well as adequate testing and consequent quarantining of high-risk contacts play leading roles in containing the virus by interrupting infection chains. This approach is especially important in the hospital setting where contacts often cannot be avoided and physical distance is usually not possible. Furthermore, health care workers (HCWs) usually have contact with a variety of vulnerable people, making it essential to identify infections among hospital employees as soon as possible to interrupt the rapid spread of SARS-CoV-2 in the facility. Several electronic tools for contact tracing, such as specific software or mobile phone apps, are available for the public health sector. In contrast, contact tracing in hospitals often has to be carried out without helpful electronic tools, and an enormous amount of human resources is typically required. AIM: For rapid contact tracing and effective infection control and management measures for HCWs in hospitals, adapted technical solutions are needed. METHODS: In this study, we report the development of our containment strategy to a web-based contact tracing and rapid point-of-care-testing workflow. RESULTS/CONCLUSION: Our workflow yielded efficient control of the rapidly evolving situation during the SARS-CoV-2 pandemic from May 2020 until January 2021 at a German University Hospital.


Subject(s)
COVID-19 Nucleic Acid Testing/methods , COVID-19/transmission , Computer Communication Networks , Contact Tracing/methods , Infectious Disease Transmission, Patient-to-Professional , Pandemics , Point-of-Care Testing , SARS-CoV-2 , COVID-19/epidemiology , Germany/epidemiology , Hospitals, University , Humans , Infection Control/methods , Infectious Disease Transmission, Professional-to-Patient/prevention & control , Mobile Applications , Personnel, Hospital , Real-Time Polymerase Chain Reaction , Retrospective Studies , Seasons , Software , Workflow
8.
Rev. gaúch. enferm ; 42(spe): e20200281, 2021. tab
Article in English | WHO COVID, LILACS (Americas) | ID: covidwho-1270964

ABSTRACT

ABSTRACT Objective Describe the development of a learning object focused on scientific evidence about COVID-19. Method Experience report on the production of a learning object based on the DADI web sites methodology, aimed at adults and children, built by nurses and academics from a Brazilian Federal University in 2020. Data collection in databases and reference organizations. Monitored performance through Google Analytics. Results Website created, "COVID-19 Evidence for All", with intuitive design and didactic language aimed at three audiences: health professionals, adult population, and children. In the first month after implementation, the website was accessed by 3,313 users, proving to be an efficient strategy for disseminating knowledge. Conclusion The development of the website involved professors, academics and master's students in the production of educational material aimed at prevention, promotion and maintenance of health. The resource allows quick consultation of the best scientific evidence available to date.


RESUMEN Objetivo Describe el desarrollo de un objeto de aprendizaje centrado en la evidencia científica sobre COVID-19. Método Informe de experiencia sobre la producción de un objeto de aprendizaje basado en la metodología de los sitios web DADI, dirigido a adultos y niños, construido por enfermeras y académicos de una Universidad Federal de Brasil, en 2020. Recopilación de datos en bases de datos y organizaciones de referencia. Rendimiento supervisado a través de Google Analytics. Resultados Sitio web creado, "Evidencia COVID-19 para todos", con diseño intuitivo y lenguaje didáctico dirigido a tres audiencias: profesionales de la salud, población adulta y niños. En el primer mes después de la implementación, el sitio fue accedido por 3.313 usuarios, demostrando ser una estrategia eficiente para diseminar conocimiento. Conclusión El desarrollo del sitio involucró a profesores, académicos y estudiantes de maestría en enfermería en la preparación de material educativo dirigido a la prevención, promoción y mantenimiento de la salud. El recurso permite una consulta rápida a las mejores recomendaciones científicas.


RESUMO Objetivo Descrever o desenvolvimento de um objeto de aprendizagem focado em evidências científicas sobre COVID-19. Método Relato de experiência sobre produção de um objeto de aprendizagem fundamentado na metodologia web sites DADI, direcionado ao público adulto e infantil, construído por enfermeiras e acadêmicos de uma Universidade Federal brasileira, em 2020. Coleta de dados em bases de dados e organizações de referências. Monitorado desempenho através do Google Analytics. Resultados Elaborado site "COVID-19 evidências para todos", com design intuitivo e linguagem didática direcionado a três públicos: profissionais de saúde, população adulta e crianças. No primeiro mês após implementação, o site foi acessado por 3.313 usuários, mostrando ser uma estratégia eficiente para disseminação de conhecimento. Conclusão O desenvolvimento do site envolveu docentes, acadêmicos e mestrandos de Enfermagem na confecção de material educativo direcionado à prevenção, promoção e manutenção da saúde. O recurso permite consulta rápida às melhores evidências científicas disponíveis até o momento.


Subject(s)
Computer Communication Networks , Knowledge , COVID-19/prevention & control , Learning , Universities , Health Education , Health Strategies , Evidence-Based Practice/education , Pandemics
9.
J Am Med Inform Assoc ; 28(8): 1765-1776, 2021 07 30.
Article in English | MEDLINE | ID: covidwho-1246728

ABSTRACT

OBJECTIVE: To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online. MATERIALS AND METHODS: We developed a distributed, federated network of 12 health systems that harmonized their EHRs and submitted aggregate answers to consortia questions posted at https://www.covid19questions.org. Our consortium developed processes and implemented distributed algorithms to produce answers to a variety of questions. We were able to generate counts, descriptive statistics, and build a multivariate, iterative regression model without centralizing individual-level data. RESULTS: Our public website contains answers to various clinical questions, a web form for users to ask questions in natural language, and a list of items that are currently pending responses. The results show, for example, that patients who were taking angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, within the year before admission, had lower unadjusted in-hospital mortality rates. We also showed that, when adjusted for, age, sex, and ethnicity were not significantly associated with mortality. We demonstrated that it is possible to answer questions about COVID-19 using EHR data from systems that have different policies and must follow various regulations, without moving data out of their health systems. DISCUSSION AND CONCLUSIONS: We present an alternative or a complement to centralized COVID-19 registries of EHR data. We can use multivariate distributed logistic regression on observations recorded in the process of care to generate results without transferring individual-level data outside the health systems.


Subject(s)
Algorithms , COVID-19 , Computer Communication Networks , Confidentiality , Electronic Health Records , Information Storage and Retrieval/methods , Natural Language Processing , Common Data Elements , Female , Humans , Logistic Models , Male , Registries
10.
J Med Libr Assoc ; 109(1): 107-111, 2021 Jan 01.
Article in English | MEDLINE | ID: covidwho-1022164

ABSTRACT

BACKGROUND: The Harvey Cushing/John Hay Whitney Medical Library serves a community of over 22,000 individuals primarily from the Yale Schools of Medicine, Public Health, and Nursing and the Yale New Haven Hospital. Though they are geographically close to one another, reaching these disparate populations can be a challenge. Having a clear and thorough communication plan has proved invaluable in transcending communication chasms, especially in recent times of crisis. CASE PRESENTATION: This article describes the Harvey Cushing/John Hay Whitney Medical Library's methods for communicating and promoting its remote resources and services in response to coronavirus disease 2019 (COVID-19). It details our communication strategies and messages leading up to, and after, the Yale campus was closed and specifies how we pivoted from reaching users inside the library to reaching our audiences remotely. CONCLUSIONS: Our communication plan has provided the foundation for all of our messaging, be it print or digital media. In recent moments of crisis, it has been especially helpful for planning and executing large scale messaging. Similarly, knowing whom to contact around our organization to promote our message in different and broader ways has been extremely beneficial.


Subject(s)
COVID-19 , Communication , Computer Communication Networks/organization & administration , Internet , Libraries, Medical/organization & administration , Adult , Aged , Aged, 80 and over , Connecticut , Female , Humans , Librarians/statistics & numerical data , Male , Middle Aged , Organizational Case Studies , SARS-CoV-2 , Students, Medical/statistics & numerical data , Young Adult
11.
J Healthc Eng ; 2020: 8838390, 2020.
Article in English | MEDLINE | ID: covidwho-999335

ABSTRACT

Background: With the outbreak of COVID-19, large-scale telemedicine applications can play an important role in the epidemic areas or less developed areas. However, the transmission of hundreds of megabytes of Sectional Medical Images (SMIs) from hospital's Intranet to the Internet has the problems of efficiency, cost, and security. This article proposes a novel lightweight sharing scheme for permitting Internet users to quickly and safely access the SMIs from a hospital using an Internet computer anywhere but without relying on a virtual private network or another complex deployment. Methods: A four-level endpoint network penetration scheme based on the existing hospital network facilities and information security rules was proposed to realize the secure and lightweight sharing of SMIs over the Internet. A "Master-Slave" interaction to the interactive characteristics of multiplanar reconstruction and maximum/minimum/average intensity projection was designed to enhance the user experience. Finally, a prototype system was established. Results: When accessing SMIs with a data size ranging from 251.6 to 307.04 MB with 200 kBps client bandwidth (extreme test), the network response time to each interactive request remained at approximately 1 s, the original SMIs were kept in the hospital, and the deployment did not require a complex process; the imaging quality and interactive experience were recognized by radiologists. Conclusions: This solution could serve Internet medicine at a low cost and may promote the diversified development of mobile medical technology. Under the current COVID-19 epidemic situation, we expect that it could play a low-cost and high-efficiency role in remote emergency support.


Subject(s)
Computer Security , Diagnostic Imaging/instrumentation , Internet , Radiology/methods , Algorithms , COVID-19 , Computer Communication Networks , Computers , Diagnostic Imaging/methods , Equipment Design , Hospitalization , Hospitals , Humans , Image Processing, Computer-Assisted/methods , Medical Informatics , Programming Languages , Telemedicine
16.
Postgrad Med J ; 97(1151): 590-597, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-913814

ABSTRACT

BACKGROUND: During the crucial time of coronavirus pandemic, education is being remodelled: opening the doors of electronic learning (e-learning). The review emphasises on the various e-learning methods that can be used in the current scenario. METHODS: The review was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines on databases, namely, PubMed, Google Scholar and Cochrane. Out of 1524 identified articles, after the process of screening and based on the eligibility criteria, 45 full-text articles were reviewed. RESULTS: Though there are many caveats on the path of successful implementation this is the right time that we step towards e-learning. The article discusses the methods and tools in e-learning that can modify the traditional ways of content delivery, record maintenance, assessment and feedback. CONCLUSION: During the period of 'planet arrest', when the whole world is locked down with the motive of social distancing, let us stay connected with e-learning.


Subject(s)
COVID-19 , Education, Distance/methods , Education, Medical/trends , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control/methods , Computer Communication Networks , Educational Technology/methods , Humans , SARS-CoV-2
17.
J Biomed Opt ; 25(10)2020 10.
Article in English | MEDLINE | ID: covidwho-889827

ABSTRACT

SIGNIFICANCE: The COVID-19 pandemic is changing the landscape of healthcare delivery in many countries, with a new shift toward remote patient monitoring (RPM). AIM: The goal of this perspective is to highlight the existing and future role of wearable and RPM optical technologies in an increasingly at-home healthcare and research environment. APPROACH: First, the specific changes occurring during the COVID-19 pandemic in healthcare delivery, regulations, and technological innovations related to RPM technologies are reviewed. Then, a review of the current state and potential future impact of optical physiological monitoring in portable and wearable formats is outlined. RESULTS: New efforts from academia, industry, and regulatory agencies are advancing and encouraging at-home, portable, and wearable physiological monitors as a growing part of healthcare delivery. It is hoped that these shifts will assist with disease diagnosis, treatment, management, recovery, and rehabilitation with minimal in-person contact. Some of these trends are likely to persist for years to come. Optical technologies already account for a large portion of RPM platforms, with a good potential for future growth. CONCLUSIONS: The biomedical optics community has a potentially large role to play in developing, testing, and commercializing new wearable and RPM technologies to meet the changing healthcare and research landscape in the COVID-19 era and beyond.


Subject(s)
Coronavirus Infections , Pandemics , Pneumonia, Viral , Telemedicine , Wearable Electronic Devices , Betacoronavirus , COVID-19 , Computer Communication Networks , Humans , Remote Sensing Technology , SARS-CoV-2
18.
J Am Med Inform Assoc ; 28(2): 360-364, 2021 02 15.
Article in English | MEDLINE | ID: covidwho-835150

ABSTRACT

OBJECTIVE: The lack of representative coronavirus disease 2019 (COVID-19) data is a bottleneck for reliable and generalizable machine learning. Data sharing is insufficient without data quality, in which source variability plays an important role. We showcase and discuss potential biases from data source variability for COVID-19 machine learning. MATERIALS AND METHODS: We used the publicly available nCov2019 dataset, including patient-level data from several countries. We aimed to the discovery and classification of severity subgroups using symptoms and comorbidities. RESULTS: Cases from the 2 countries with the highest prevalence were divided into separate subgroups with distinct severity manifestations. This variability can reduce the representativeness of training data with respect the model target populations and increase model complexity at risk of overfitting. CONCLUSIONS: Data source variability is a potential contributor to bias in distributed research networks. We call for systematic assessment and reporting of data source variability and data quality in COVID-19 data sharing, as key information for reliable and generalizable machine learning.


Subject(s)
COVID-19 , Data Accuracy , Datasets as Topic , Information Dissemination , Machine Learning , Adult , Aged , COVID-19/classification , Computer Communication Networks , Datasets as Topic/standards , Female , Humans , Male , Middle Aged , Patient Acuity
20.
J Am Med Inform Assoc ; 27(6): 934-938, 2020 06 01.
Article in English | MEDLINE | ID: covidwho-596564

ABSTRACT

The epidemic of coronavirus disease 2019 (COVID-19) broke out in Wuhan, China, in early 2020. In an effort to curb the spread of the epidemic, the government has requisitioned a variety of venues and plant buildings and built more than 20 cabin hospitals to receive patients with mild symptoms within 48 hours. Under this circumstance, we worked out a 5G all-wireless solution to divide the overall network system of the cabin hospital into multiple network units by function. While ensuring good signal coverage of the local unit, each network unit was independently connected to the host hospital's data center over a virtual private network (VPN) tunnel built on the 5G wireless network. Our successful experience with the application of this 5G + VPN all-wireless network system well points to the bright prospect of 5G wireless network. In addition, the 5G + VPN solution can also be used for multihospital network interconnection and rapid network recovery during the failure of wired network.


Subject(s)
Betacoronavirus , Cell Phone , Computer Communication Networks , Coronavirus Infections/epidemiology , Hospital Information Systems , Pneumonia, Viral/epidemiology , Telemedicine , Wireless Technology , COVID-19 , China/epidemiology , Electronic Health Records , Epidemics/prevention & control , Humans , Mobile Health Units , Organizational Case Studies , Pandemics , SARS-CoV-2
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