Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 72
Filter
1.
International Journal of Emerging Technologies in Learning ; 17(21):230-245, 2022.
Article in English | Web of Science | ID: covidwho-2201273

ABSTRACT

A remote lab is a technology that allows participants to efficiently conduct experimental teaching where users can connect to lab equipment from anywhere without being in a specific physical location. The COVID-19 pandemic affects all areas of human activity. As a result, students did not receive face-to-face instruction, and access to the laboratory was limited or practically impos-sible, and access to laboratory facilities has been limited or nearly impossible. Especially in engineering education, students' practical abilities cannot be devel-oped comprehensively. In this paper, this paper built an online remote robotics experiment system using digital twin (DT) technology and IoT technology and adopted ADDIE (Analysis, Design, Development, Implementation, and Evalua-tion) teaching method. With these measures, students can design and debug robot programs at home, just like in the laboratory. This study sent questionnaires to 64 students, and 58 were returned. The results show that more than 80% of students believe that the remote labs for industrial robotics courses have improved the efficiency and quality of students' skills training as opposed to virtual simulation and watching videos on the computer.

2.
Annual review of public health. ; 10, 2022.
Article in English | EMBASE | ID: covidwho-2194165

ABSTRACT

Public health surveillance is defined as the ongoing, systematic collection, analysis, and interpretation of health data and is closely integrated with the timely dissemination of information that the public needs to know and upon which the public should act. Public health surveillance is central to modern public health practice by contributing data and information usually through a national notifiable disease reporting system (NNDRS). Although early identification and prediction of future disease trends may be technically feasible, more work is needed to improve accuracy so that policy makers can use these predictions to guide prevention and control efforts. In this article, we review the advantages and limitations of the current NNDRS in most countries, discuss some lessons learned about prevention and control from the first wave of COVID-19, and describe some technological innovations in public health surveillance, including geographic information systems (GIS), spatial modeling, artificial intelligence, information technology, data science, and the digital twin method. We conclude that the technology-driven innovative public health surveillance systems are expected to further improve the timeliness, completeness, and accuracy of case reporting during outbreaks and also enhance feedback and transparency, whereby all stakeholders should receive actionable information on control and be able to limit disease risk earlier than ever before. Expected final online publication date for the Annual Review of Public Health, Volume 44 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

3.
33rd IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2022 ; 2022-September, 2022.
Article in English | Scopus | ID: covidwho-2192047

ABSTRACT

With COVID-19 as an initiation, the stage for human socioeconomic activities is rapidly shifting from physical space to cyberspace. Mobile networks have evolved as essential communication networks for connecting individuals and things to the cloud. Further evolution of mobile networks is essential to realize Digital Twin. In particular, low latency and guaranteed QoS using network slicing are extremely challenging requirements that legacy mobile networks until 4G have not been able to meet. In addition, the chronic shortage of spectrum accompanying the shift to broadband continues to encourage the use of small cells, which naturally make xHaul1 denotes a term that expresses either fronthaul, midhaul or backhaul. problem be more serious. The author has worked on this xHaul problem in both academia and industry for 20 years, developing a unique WLAN mesh protocol for backhaul. In order to bring the results of this research to practical use, PicoCELA Inc. as a vehicle for commercialization of the fruits, was incorporated. The edge device brought by PicoCELA with the WLAN mesh capability are linked to a cloud server and are serving various applications as a general-purpose platform to facilitate the introduction of Digital Twin. This paper reviews the history of WLAN mesh technology to date, identifies the technical issues that arise when using it in an enterprise scenario, and then provides an overview of how PicoCELA' s WLAN mesh addresses these issues. The PicoCELA solution as an edge platform is overviewed, followed by some real-world use cases. Finally, the outlook for mobile communications in the future is summarized. © 2022 IEEE.

4.
Ieee Access ; 10:134623-134646, 2022.
Article in English | Web of Science | ID: covidwho-2191672

ABSTRACT

Over the past two years, the spread of COVID-19 has spurred the use of information and communication technologies (ICT) in aid of healthcare. The need to guarantee continuity to care has promoted research and industry activities aimed at developing solutions for the digitalization of the procedures to be performed to provide health services, even in emergency scenarios. Digital collection, transmission, and processing of health data represent the starting point for fulfilling this innovation process but also bring heterogeneous challenges. These motivations led to the elaboration of this work, which analyzes innovative and technological tools for the development of digital health (eHealth) through the collection of multisectoral literature, produced thanks to the cooperation of varied research groups, thus providing a multidisciplinary survey. Since digital health is expected to be one of the leading applications of the sixth-generation (6G) wireless cellular networks, this paper covers the related telecommunications aspects. Furthermore, the exploitation of artificial intelligence paradigms to elaborate massive amounts of biological data is examined. Given the extreme sensitivity of health data, this paper also investigates security and privacy issues. In particular, the main techniques and approaches to guarantee security properties (i.e., anonymity, responsibility, authentication, confidentiality, integrity, non-repudiation, and revocability) are studied. Applications involving innovative electromagnetic systems for healthcare and assisted living services are described to provide an example of an eHealth scenario leveraging ICT. Finally, the telemedicine-related regulations of the European Commission are analyzed, with particular reference to the General Data Protection Regulation (GDPR).

5.
Advances in Science, Technology and Innovation ; : 103-113, 2022.
Article in English | Scopus | ID: covidwho-2173603

ABSTRACT

The attention of the architecture, engineering, construction and operation (AECO) industry has been shifting from a great interest in the design and construction phases to the facility management (FM) and operational phase over the last decade. Disruptive technologies, such as information and communication technology (ICT), Internet of things (IoT) and building information modelling (BIM) have shown promising application to achieve a connected and effective management of buildings. Due to issues, such as COVID-19 and energy waste, governments have started promoting smart working to both private and public organisations. The expected benefits are twofold, namely social distancing in offices and better management of costs and spaces. This paper aims to define a digital twin-based system for smart management of office spaces. The system will help organisations to better manage their real estate and provide a basis for the development of a management platform. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

6.
International Journal of Online and Biomedical Engineering ; 18(14):28-41, 2022.
Article in English | Web of Science | ID: covidwho-2163800

ABSTRACT

During the coronavirus crisis, labs had to be offered in digital form in mechanical engineering at short notice. For this purpose, digital twins of more complex test benches in the field of fluid energy machines were used in the mechanical engineering course, with which the students were able to interact remotely to obtain measurement data. The concept of the respective lab was revised with regard to its implementation as a remote laboratory. Fortunately, real-world labs were able to be fully replaced by remote labs. Student perceptions of remote labs were mostly positive. This paper explains the concept and design of the digital twins and the lab as well as the layout, procedure, and finally the results of the accompanying evaluation. However, the implementation of the digital twins to date does not yet include features which address the tactile experience of working in real-world labs.

7.
30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022 ; : 1257-1268, 2022.
Article in English | Scopus | ID: covidwho-2162008

ABSTRACT

Digital twins are increasingly developed to support the development, operation, and maintenance of cyber-physical systems such as industrial elevators. However, industrial elevators continuously evolve due to changes in physical installations, introducing new software features, updating existing ones, and making changes due to regulations (e.g., enforcing restricted elevator capacity due to COVID-19), etc. Thus, digital twin functionalities (often built on neural network-based models) need to evolve themselves constantly to be synchronized with the industrial elevators. Such an evolution is preferred to be automated, as manual evolution is time-consuming and error-prone. Moreover, collecting sufficient data to re-train neural network models of digital twins could be expensive or even infeasible. To this end, we propose unceRtaInty-aware tranSfer lEarning enriched Digital Twins LATTICE, a transfer learning based approach capable of transferring knowledge about the waiting time prediction capability of a digital twin of an industrial elevator across different scenarios. LATTICE also leverages uncertainty quantification to further improve its effectiveness. To evaluate LATTICE, we conducted experiments with 10 versions of an elevator dispatching software from Orona, Spain, which are deployed in a Software in the Loop (SiL) environment. Experiment results show that LATTICE, on average, improves the Mean Squared Error by 13.131% and the utilization of uncertainty quantification further improves it by 2.71%. © 2022 ACM.

8.
1st International Conference on Technology Innovation and Its Applications, ICTIIA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2161424

ABSTRACT

The purpose of this article is to explore the impact of Digital Twin technology on the realm of health. The topic is carried out by referencing the function of Digital Twin in ailments that are often seen in modern culture. The role of Digital Twin in the improvement of lung diseases and diabetes treatment especially in the COVID-19 pandemic era, and in the creation of smart hospitals that are expected to become the major hospital system in the future are discussed in this article. Additionally, this article will address the effect of the Digital Twin on the creation of management systems in the world of health, as it serves as a standard for the health world's future. © 2022 IEEE.

9.
International Conference on Data Analytics, Intelligent Computing, and Cyber Security, ICDIC 2020 ; 315:439-445, 2023.
Article in English | Scopus | ID: covidwho-2148664

ABSTRACT

Digital twins for factories and processes are becoming more prevalent and more valuable as a result of recent technological breakthroughs and the rise of smart manufacturing. There are also more potential for closed-loop analytics with digital twins, as well as with the rise of connection, data storage, and the Industrial Internet of Things (IIoT). Some factories have employed discrete event simulations (DES) to construct digital twins that are connected to the manufacturing floor and can be monitored in real time. However, it is difficult to quantify the advantages of a digital twin that is linked to the real world. With the emergence of the new generation of mobile network (5G), Tactile Internet, as well as the deployment of Industry 4.0 and Health 4.0, multimedia systems are moving towards immersed haptic-enabled human–machine interaction systems such as the digital twin (DT). Specifically, Industry 4.0 will be using DT and robots on a large scale. This will increase human–machine and interaction to a great extent. There will be multimodal communications used to interact with digital twins and robots, especially haptics. Hence, Tactile Internet will replace the conventional Internet today. In fact, a DT system can also be extended in Health 4.0 domain to act as a COVID-19 is a COVID-19 early warning system. When a person's temperature and other symptom data are tracked in real time, it may be determined whether or not it is time to see a doctor or undergo a COVID examination. In conjunction with a COVID tracing programme, the digital twin may be able to provide further information about the virus in relation to the individual. Since there are currently no well-recognized models to evaluate the performance of these systems, to address this research lacuna, we proposed a Quality of Experience (QoE) model for DT systems con-training multi-levels of subjective, objective, and physiopsychological influencing factors. The model is itemized through a fully detailed taxonomy that deduces the perceived user’s emotional and physical states during and after consuming spatial, temporal, proximal, and ed multi-modality media between humans and machines. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

10.
24th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020 ; 13753 LNAI:314-330, 2023.
Article in English | Scopus | ID: covidwho-2148644

ABSTRACT

Predicting the evolution of the Covid-19 pandemic during its early phases was relatively easy as its dynamics were governed by few influencing factors that included a single dominant virus variant and the demographic characteristics of a given area. Several models based on a wide variety of techniques were developed for this purpose. Their prediction accuracy started deteriorating as the number of influencing factors and their interrelationships grew over time. With the pandemic evolving in a highly heterogeneous way across individual countries, states, and even individual cities, there emerged a need for a contextual and fine-grained understanding of the pandemic to come up with effective means of pandemic control. This paper presents a fine-grained model for predicting and controlling Covid-19 in a large city. Our approach borrows ideas from complex adaptive system-of-systems paradigm and adopts a concept of agent as the core modeling ion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

11.
Front Public Health ; 10: 1016680, 2022.
Article in English | MEDLINE | ID: covidwho-2142349

ABSTRACT

Cognitive decline is a gradual neurodegenerative process that is affected by genetic and environmental factors. The doctor-patient relationship in the healthcare for cognitive decline is in a "shallow" medical world. With the development of data science, virtual reality, artificial intelligence, and digital twin, the introduction of the concept of the metaverse in medicine has brought alternative and complementary strategies in the intervention of cognitive decline. This article technically analyzes the application scenarios and paradigms of the metaverse in medicine in the field of mental health, such as hospital management, diagnosis, prediction, prevention, rehabilitation, progression delay, assisting life, companionship, and supervision. The metaverse in medicine has made primary progress in education, immersive consultation, dental disease, and Parkinson's disease, bringing revolutionary prospects for non-pharmacological complementary treatment of cognitive decline and other mental problems. In particular, with the demand for non-face-to-face communication generated by the global COVID-19 epidemic, the needs for uncontactable healthcare service for the elderly have increased. The paradigm of self-monitoring, self-healing, and healthcare experienced by the elderly through the metaverse in medicine, especially from meta-platform, meta-community, and meta-hospital, will be generated, which will reconstruct the service modes for the elderly people. The future map of the metaverse in medicine is huge, which depends on the co-construction of community partners.


Subject(s)
COVID-19 , Cognitive Dysfunction , Humans , Aged , Physician-Patient Relations , Artificial Intelligence , Cognitive Dysfunction/therapy , Mental Health
12.
20th International Conference on Practical Applications of Agents and Multi-Agent Systems , PAAMS 2022 ; 13616 LNAI:24-35, 2022.
Article in English | Scopus | ID: covidwho-2128472

ABSTRACT

Open economy, globalization and effect of Covid19 pandemic are transforming the consumer behavior rapidly. The business is nudging consumers towards hyper consumption through online shopping, e-commerce and other conveniences with affordable cost. The companies from courier, express and parcel (CEP) industry are trying to capitalize on this opportunity by tying up with business to consumers (B2C) companies with a promise of delivering parcels to the doorstep in an ever-shrinking time window. In this endeavor, the conventional optimization-based planning approach to manage the fixed parcel payload is turning out to be inadequate. The CEP companies need to quickly adapt to the situation more frequently so as to be efficient and resilient in this growing demand situation. We propose an agent-based digital twin of the sorting terminal, a key processing element of parcel delivery operation, as an experimentation aid to: (i) explore and arrive at the right configuration of the existing sorting terminal infrastructure, (ii) be prepared for possible outlier conditions, and (iii) identify plausible solutions for mitigating the outlier conditions in an evidence-backed manner. This paper presents digital twin of the sorting terminal and demonstrates its use as “in silico” experimentation aid for domain experts to support evidence-backed decision-making. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

13.
ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition, GT 2022 ; 5, 2022.
Article in English | Scopus | ID: covidwho-2137305

ABSTRACT

In the project IoT for Supervision and Control of Water Systems (IoT.H2O) the potential of the Internet of Things concept for operating pump systems is investigated. As a result of the project, a pump test rig which can be controlled by an open source IoT platform was developed. Because of COVID 19 students are currently not able to access the test rig in their laboratory class. In the paper, a virtual pump test rig is presented. The model of the test rig is based on the physical IoT pump test rig and consists of models for pump, control valve, piping system and electric motor. By modeling the electric motor, the operating behavior of the pump becomes much more realistic since effects of inertia can be included. The communication of the IoT platform with the model is based on the MQTT protocol and is identical to the real rig. The test rig can be operated with any web browser through a dashboard. On the dashboard, the operating frequency of the electric motor, the control valve position, the static head of the system and the tank pressure before the pump can be set with predefined control widgets which are already available in the IoT platform. Also, through buttons, measurements of speed, static pressure and torque are possible. The data can be downloaded after the measurements are taken. In different assignments, the students, can measure the head and efficiency curves and system curves and compare speed control and throttle control. Also, different types of pumps can be assessed easily by exchanging the pump curves in the model. A big advantage of the virtual lab tests is that the students can run the tests by themselves and obtain their own data. Before, the tests were only run in groups because of time constraints. Based on the laboratory class, they are able to assess the behavior of pumps in systems and to design pump systems efficiently. Also, they are introduced to the concept of IoT. © 2022 American Society of Mechanical Engineers (ASME). All rights reserved.

14.
26th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2022 ; : 168-174, 2022.
Article in English | Scopus | ID: covidwho-2136155

ABSTRACT

In order to monitor and assess the spread of the Omicron variant of COVID-19, we propose a Distributed Digital Twin that virtually mirrors a hemodialysis unit in a hospital in Toronto, Canada. Since the solution involves heterogeneous components, we rely on the IEEE HLA distributed simulation standard. Based on the standard, we use an agent-based/discrete event simulator together with a virtual reality environment in order to provide to the medical staff an immersive experience that incorporates a platform showing predictive analytics during a simulation run. This can help professionals monitor the number of exposed, symptomatic, asymptomatic, recovered, and deceased agents. Agents are modeled using a redesigned version of the susceptible-exposed-infected-recovered (SEIR) model. A contact matrix is generated to help identify those agents that increase the risk of the virus transmission within the unit. © 2022 IEEE.

15.
Environment and Planning B: Urban Analytics and City Science ; 2022.
Article in English | Web of Science | ID: covidwho-2123305

ABSTRACT

Complexity theory has become a conceptual framework and a source of inspiration for Smart City initiatives. In addition to many other conceptions, the Urban Digital Twin (UDT) became both a concept and a tool for generating the revolutionary act of data-driven 3D city modeling. Indeed, the UDT has increased the ability of planners to make decisions vis-a-vis data-driven city models;at the same time, however, it has attracted criticism because of its focus on the physical dimensions of cities. In facing these challenges, we seek to join the conceptual and practical efforts to generate a social turn in the field of Smart Cities and urban innovation. Creating a UDT with a social focus, we maintain, is not only a 1:1 translation of the built environment into the social realm, but also demands interdisciplinary knowledge from the fields of sociology, anthropology, planning, and ethics studies. This article makes theoretical and methodological contributions. Theoretically, it discusses the potential contribution of the Social Urban Digital Twin (SUDT) to the theory of urbanism, enabling us to represent the physical and the social environments as a single fabric. Methodologically, it enhances the know-how of the City Analytics research community by advancing a six-phase protocol for developing SUDTs, each phase of which integrates technological conceptions and social-theoretical content. The phases of the SUDT protocol are demonstrated using a specific case study: the experience of elderly residents of the Haifa neighborhood of Hadar-a low-income neighborhood in Israel characterized by ethnic and national diversity-during the Coronavirus pandemic. We conclude by discussing the contributions and limitations of the SUDT.

16.
Robotics and Computer-Integrated Manufacturing ; 80:102489, 2023.
Article in English | ScienceDirect | ID: covidwho-2120209

ABSTRACT

Affected by COVID-19, the maintenance process of machine tools is significantly hindered, while unmanned maintenance becomes an emerging trend in such background. So far, three challenges, namely, the dependence on maintenance experts, the dynamic maintenance environments, and unsynchronized interactions between physical and information sides, exist as the main obstacles in its widespread applications. In order to fill this gap, a bio-inspired LIDA cognitive-based Digital Twin architecture is proposed, so as to achieve unmanned maintenance of machine tools through a self-constructed, self-evaluated, and self-optimized manner. A three phases process in the architecture, including the physical phase, virtual phase, and service phase, is further introduced to support the cognitive cycle for unmanned maintenance of machine tools. An illustrative example is depicted in the unmanned fault diagnosis on the rolling bearing of a drilling platform, which validates the feasibility and advantages of the proposed architecture. As an explorative study, it is wished that this work provides useful insights for unmanned maintenance of machine tools in a dynamic production environment.

17.
Sensors (Basel) ; 22(21)2022 Nov 01.
Article in English | MEDLINE | ID: covidwho-2099737

ABSTRACT

The rapid growth of the world population has increased the food demand as well as the need for assurance of food quality, safety, and sustainability. However, food security can easily be compromised by not only natural hazards but also changes in food preferences, political conflicts, and food frauds. In order to contribute to building a more sustainable food system-digitally visible and processes measurable-within this review, we summarized currently available evidence for various information and communication technologies (ICTs) that can be utilized to support collaborative actions, prevent fraudulent activities, and remotely perform real-time monitoring, which has become essential, especially during the COVID-19 pandemic. The Internet of Everything, 6G, blockchain, artificial intelligence, and digital twin are gaining significant attention in recent years in anticipation of leveraging the creativity of human experts in collaboration with efficient, intelligent, and accurate machines, but with limited consideration in the food supply chain. Therefore, this paper provided a thorough review of the food system by showing how various ICT tools can help sense and quantify the food system and highlighting the key enhancements that Industry 5.0 technologies can bring. The vulnerability of the food system can be effectively mitigated with the utilization of various ICTs depending on not only the nature and severity of crisis but also the specificity of the food supply chain. There are numerous ways of implementing these technologies, and they are continuously evolving.


Subject(s)
Blockchain , COVID-19 , Humans , Pandemics/prevention & control , Artificial Intelligence , Food Security
18.
Ifac Papersonline ; 55(17):338-343, 2022.
Article in English | Web of Science | ID: covidwho-2095446

ABSTRACT

This paper deals with an application developed with MATLAB at the Universite Claude Bernard Lyon 1, France, for any user to be able to learn GRAFCET with numerical experiments without any automation hardware or real system. It has been designed during the COVID'19 lockdown to be easy to use for students with weak experience with computer programming (assuming few hours already spent on MATLAB) and assuming to have followed the basic course on logic systems and GRAFCET for a few hours. The user defined parts of the application is concerned with few MATLAB script files (with existing examples) to define his/her own input/output variables and his/her own GRAFCET. A Graphical User Interface (GUI) allows to play with two examples: A simple toy example with 5 input/output variables where the user can learn how to translate his/her "paper" GRAFCET solution into this application and how to use the GUI to run simulations for final GRAFCET evaluations. The second available system is a 4 floor lift based on 30 input/output variables which is a more complex example to focus to evaluate the user. For each example a digital twin is also available (its development is not a part of the user work) to update the state of underlying continuous variables and logic measures needed for the evolution inside the GRAFCET based on the state of the system actions updated by the GRAFCET. Other digital twin of systems and/or user defined GRAFCET may be added in the application. Copyright (C) 2022 The Authors.

19.
Chest ; 162(4):A1454, 2022.
Article in English | EMBASE | ID: covidwho-2060818

ABSTRACT

SESSION TITLE: Use of Machine Learning and Artificial Intelligence SESSION TYPE: Original Investigations PRESENTED ON: 10/16/22 10:30 am - 11:30 am PURPOSE: The COVID-19 pandemic has significantly impacted the US healthcare system. Between March 1, 2020, and January 2, 2021, a 22.9% increase in all-cause mortality was reported [1]. We used Artificial Intelligence (AI) for data analysis to have a prototype national average by matching various characteristics. This is a novel approach known as Digital Twinning Method (DTM). We intend to compare non-COVID mortality between 2020 and 2019 using this DTM approach. METHODS: Data was collected by a contracted vendor that provided analysis utilizing an AI framework. Mortality rates were calculated at four points of care categorized as 1) In-patient mortality, 2) 30-day on-admission, 3) 30-day on discharge, and 4) 90-day on-admission. Baseline risk predictions were generated using DTM for matching patient demographics such as age, gender, race, Medicare status, and community-dwelling status. Hence, each person was compared to a "twin” with the same risk of hospitalization, death, acute myocardial infarction, or stroke. RESULTS: Our institution had a higher actual non-COVID mortality in 2020 compared to the actual mortality in 2019 across all four points of care studied. The highest increase was noticed in the 90-day on-admission category (9.7% in 2019 vs 12.6% in 2020) followed by 30-day on-admission (5.0% in 2019, to 6.6% in 2020), 30-day on-discharge (4.2% in 2019, to 5.7% in 2020), and in-patient mortality (1.8% in 2019, to 2.6% in 2020). However, when compared to twinned patients at other hospitals, our institution had a lower non-COVID mortality rate across all categories in 2019 and 2020. We utilized the Sign Test to evaluate our repeated-paired-measures for the above four points of care categories during two different conditions, i.e., under a normal healthcare situation (2019) and in the pandemic year (2020). Our two-tailed p-value was 0.0455 with statistical significance at p < 0.05, with M1-M2 (M=measure) difference of -0.8 (in-patient mortality), -1.6 (30 day on-admission), -1.5 (30 day on-discharge), and -2.9 (90 day on-admission) for the four categories. Our z-score was +2 under the formula z = (X - pn) / √npq, signifying positive deviation from the mean. Our study was limited by the unavailable data of patients who may have had COVID but were undiagnosed. CONCLUSIONS: AI is a novel method to obtain reliable data. Based on our results, we conclude that the non-COVID mortality rate at our institution increased during the pandemic. Further studies are needed to specify the underlying causes attributable to the increased mortality. CLINICAL IMPLICATIONS: By leveraging Artificial intelligence in healthcare to analyze big datasets and perform complex analyses, it may be of clinical importance to utilize AI-generated risk prediction models to accurately identify variables that can be controlled in future pandemics to decrease mortality while increasing overall efficiency of the healthcare system. DISCLOSURES: No relevant relationships by Muhammad Mohsin Abid No relevant relationships by Sana Jogezai No relevant relationships by Iqbal Ratnani No relevant relationships by Muhammad Hassan Virk No relevant relationships by Anza Zahid

20.
Chest ; 162(4):A746, 2022.
Article in English | EMBASE | ID: covidwho-2060680

ABSTRACT

SESSION TITLE: Optimizing Resources in the ICU SESSION TYPE: Original Investigations PRESENTED ON: 10/16/2022 10:30 am - 11:30 am PURPOSE: The COVID-19 pandemic has exposed worldwide heterogeneity in the application of fundamental critical care principles and best practices. New methods and strategies to facilitate timely and accurate interventions are needed. If built on a robust foundation of physiologic principles, a virtual critically ill patient (aka digital twin) could better inform decision making in critical care. When used in clinical practice, a digital twin may allow bedside providers to preview how organ systems interact to cause a clinical effect, providing the opportunity to test the effects of various interventions virtually, without exposing an actual patient to potential harm. Building on our previous work with a digital twin model of critically ill patients with sepsis, this current project focuses specifically on the respiratory system. METHODS: We assembled a modified Delphi panel of 36 international critical care experts. We modeled elements of respiratory system pathophysiology using directed acyclic graphs (DAG) and derived several statements describing associated ICU clinical processes. Panelists participated in three Delphi rounds to gauge agreement on 71 final statements using a 6-point Likert scale. Agreement was defined as >80% selection of a 5 (“agree”) or 6 (“strongly agree”). RESULTS: The first Delphi round included statements of pulmonary physiology affecting critically ill patients, eg pulmonary edema, hypoxemic and hypercapnic respiratory failure, shock, acute respiratory distress syndrome (ARDS), airway obstruction, restrictive lung disease, and ventilation-perfusion mismatch. Agreement was achieved on 60 (84.5%) of expert statements after completion of two rounds. After partial completion of the third round, agreement increased to 62 (87%). Statements with the most agreement included the physiology and management of airway obstruction decreasing alveolar ventilation and the effects of alveolar infiltrates on ventilation-perfusion matching. Lowest agreement was noted for the statements describing the interaction between shock and hypoxemic respiratory failure due to increased oxygen consumption and ARDS increasing dead space. CONCLUSIONS: An international cohort of critical care experts reached 87% agreement on our rule statements for respiratory system pathophysiology. The Delphi approach appears to be an effective way to refine content for our digital twin model. CLINICAL IMPLICATIONS: Expert consensus can be used to strengthen the respiratory physiology statements used to direct the ICU digital twin patient model. With a digital twin based on refined respiratory physiology statements, bedside providers may preview how organ systems interact to cause a clinical effect without exposing an actual patient to various interventions. DISCLOSURES: No relevant relationships by Ognjen Gajic, value=Royalty Removed 06/06/2022 by Ognjen Gajic No relevant relationships by Amos Lal No relevant relationships by John Litell No relevant relationships by Amy Montgomery

SELECTION OF CITATIONS
SEARCH DETAIL