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Ubiquitous environments are not fixed in time. Entities are constantly evolving;they are dynamic. Ubiquitous applications therefore have a strong need to adapt during their execution and react to the context changes, and developing ubiquitous applications is still complex. The use of the separation of needs and model-driven engineering present the promising solutions adopted in this approach to resolve this complexity. The authors thought that the best way to improve efficiency was to make these models intelligent. That's why they decided to propose an architecture combining machine learning with the domain of modeling. In this article, a novel tool is proposed for the design of ubiquitous applications, associated with a graphical modeling editor with a drag-drop palette, which will allow to instantiate in a graphical way in order to obtain platform independent model, which will be transformed into platform specific model using Acceleo language. The validity of the proposed framework has been demonstrated via a case study of COVID-19. © 2023 IGI Global. All rights reserved.
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The adoption of the Internet of Things (IoT) has revolutionized the way the health care industry works. IoT en-abled smart and connected solutions like smart sensors, wearable devices, and smart health monitoring systems are used to unleash the potential growth of the health care industry. IoT based health care solutions are on greater priority among IoT service providers since the disruptions caused by the COVID-19. According to experts, there still exist white spots in research studies on the Internet of Things (IoT) and health care Systems. The study conducted in this paper aims to explore emerging global research trends and topical focus in the field of IoT in health care System. Bibliometric analysis is used to analyze the research articles on 'Internet of Things' and 'Health care Systems' extracted from SCOPUS and WoS database using VoS Viewer tool;the analysis used to assess the growth and research trends of different research fields over a period of time. The parameters considered during analysis include year-wise citations, year-wise publications, keyword clustering analysis, author-wise analysis, country-wise research trends and publication trend over the years. The results showcased that there has been significant change in utilization of IoT in healthcare systems continuously during the period under study conducted. © 2022 IEEE.
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The study analyzed available literatures covering the organization of measures to combat the COVID-19 pandemic in the healthcare systems of the Russian Federation and several foreign countries. For the comprehensive assessment of the specifics of organizing measures to combat the COVID-19 pandemic, countries were chosen based on geographical distances from China (the closest is Korea, and the most remote are the Great Britain and Haiti), maximum population on their continent (the United States is in North America, and Brazil in South America), and significant differences in the functioning of the healthcare systems. The peculiarities of organizing measures to combat the COVID-19 pandemic in the considered countries were associated with a complex of political, financial, economic, demographic, and organizational factors, the individual combination of which determined the peculiarities of the development of the epidemic process in each specific case. Moreover, as a priority manifestation of the severity of these factors, the capabilities of the healthcare system, including the availability of services of medical workers, sufficient number of testing equipment, medical protection equipment, hospital beds, and other parameters, should be considered. The main role was played by global state strategies implemented in the healthcare systems of the analyzed countries at the pre-epidemic stage and, in most cases, aimed at optimizing the financial and economic provisions of state guarantees of medical care. The general criteria for the differential diagnosis of COVID-19 in the national recommendations of all the states considered were respiratory symptoms and general infectious intoxication. In addition, fever and respiratory symptoms were accepted as priority criteria for COVID-19 screening. © 2023 Vestnik Rossijskoj Voenno-Medicinskoj Akademii. All rights reserved.
ABSTRACT
The concept of chronic kidney disease (CKD) originated in the 2000s, and an estimated 850 million patients are currently suffering from health threats from different degrees of CKD. However, it is unclear whether the existing CKD care systems are optimal for improving patient prognosis and outcomes, so this review summarizes the burden, existing care models, effectiveness, challenges, and developments of CKD care. Even under the general care principles, there are still significant gaps in our understanding of the causes of CKD, prevention or care resources, and care burdens between countries worldwide. Receiving care from multidisciplinary teams rather than only a nephrologist shows potential profits in comprehensive and preferable outcomes. In addition, we propose a novel CKD care structure that combines modern technologies, biosensors, longitudinal data visualization, machine learning algorithms, and mobile care. The novel care structure could simultaneously change the care process, significantly reduce human contact, and make the vulnerable population less likely to be exposed to infectious diseases such as COVID-19. The information offered should be beneficial, allowing us to rethink future CKD care models and applications to reach the goals of health equality and sustainability.
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Despite the significant achievements of current healthcare systems (CHCSs) in curing or treating several acute conditions, there has been far less success coping with noncommunicable diseases (NCDs), which have complex roots and nonconventional transmission vectors. Owing to the impact of the invisible hyperendemic NCDs and the COVID-19 pandemic, the limitations of CHCSs have been exposed. In contrast, the advent of omics-based technologies and big data science has raised global hope of curing or treating NCDs and improving overall healthcare outcomes. However, challenges related to their use and effectiveness must be addressed. Additionally, while such advancements intend to improve quality of life, they can also contribute the ever-increasing health disparity among vulnerable populations, such as low/middle-income populations, poorly educated people, gender-based violence victims, and minority and indigenous peoples, to name a few. Among five health determinants, the contribution of medical care to individual health does not exceed 11%. Therefore, it is time to implement a new well-being-oriented system complementary or parallel to CHCSs that incorporates all five health determinants to tackle NCDs and unforeseen diseases of the future, as well as to promote cost-effective, accessible, and sustainable healthy lifestyle choices that can reduce the current level of healthcare inequity.
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Introduction: The outbreak of the COVID-19 pandemic was a period of uncertainty and stress for healthcare managers due to the lack of knowledge (about the transmission of the virus, etc.) and also due to the lack of uniform organisational and treatment procedures. It was a period where the ability to prepare for a crisis, to adapt to the existing conditions, and to draw conclusions from the situation were of critical importance to keep ICUs (intensive care units) operating. The aim of this project is to compare the pandemic response to COVID-19 in Poland during the first and second waves of the pandemic. This comparison will be used to identify the strengths and weaknesses of the response, including challenges presented to health professionals and health systems and ICUs with COVID-19 patients according to the European Union Resilience Model (2014) and the WHO Resilience Model (2020). The WHO Resilience model was suitable to the COVID-19 situation because it was developed based on this experience. Methods: A matrix of 6 elements and 13 standards assigned to them was created using the EC and WHO resilience guidelines. Results: Good governance in resilient systems ensures access to all resources without constraints, free and transparent flow of information, and a sufficient number of well-motivated human resources. Conclusions: Appropriate preparation, adaptation to the existing situation, and effective management of crisis situations are important elements of ensuring the resilience of ICUs.
Subject(s)
COVID-19 , Humans , Pandemics , SARS-CoV-2 , Delivery of Health Care , Health PersonnelABSTRACT
Today, social and healthcare systems at a global level are facing constant challenges dictated by an increasing mismatch between the demand for care services and the supply of human and economic resources. Such a situation has been exacerbated in the past two years by the Covid-19 pandemic. This has led to an increase in the leverage of digitalisation, which has proved to be a crucial tool for the development and application of new organisational models at both hospital and territorial levels, thus addressing the various criticalities already present in the system. In this sense, the Virtual Hospital has emerged as a potential model for increasing effectiveness and efficiency in delivering sociomedical services. Starting from these premises, an EFTE (estimate, feedback, talk, estimate) approach was used to acquire an expert consensus within a multidisciplinary panel of academics and healthcare managers of the Veneto Region in Italy. This article reports the expert opinion on the possible application of the Virtual Hospital model in the national context, starting from the existing international evidence and good practices, highlighting the potential advantages and barriers to its implementation. Furthermore, the article analyses the most relevant areas of investment for the development of intangible assets and the acquisition of tangible assets necessary for its implementation.
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At the turn of the century, the National Health Service (NHS) in the United Kingdom (UK) was considered one of the top public healthcare systems in the world. Not only was it comprehensive and inclusive, but it was also free at the point of delivery for the entire UK population. It was also largely available to visitors and the families of residents that lived outside the UK. During the past 30 years, the NHS has received more and more funding both in cash terms and as a percentage of the gross national product. Despite this, the general consensus is that the NHS is delivering a poor service. The current government is facing unprecedented strike action from all areas of the workforce including doctors and nurses. This editorial asks the following questions: Where has the money gone? What has caused the current crisis? Can the current NHS model survive in today's highly technological healthcare environment?
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The COVID-19 pandemic has placed an unprecedented burden on the healthcare system. In particular, the intersection of COVID-19 and cancer has created a double burden on the healthcare system, presenting challenges in both the diagnosis and treatment of cancer. During the pandemic, overcrowding of hospitals and clinics, shortages of personal protective equipment (PPE) and other medical supplies, and the impact of COVID-19 on healthcare workers have all made it more difficult to care for cancer patients. The challenges in cancer diagnosis and screening during the pandemic have included delays in cancer diagnoses, decreased access to cancer screenings, and a decrease in the number of cancer surgeries being performed. Changes in cancer treatment patterns and access to care during COVID-19 have also impacted the treatment outcomes for cancer patients, with a decrease in the number of cancer patients being treated and an increased risk of poor outcomes for those who are being treated. The impact of COVID-19 on healthcare workers and their ability to care for cancer patients has also been significant, with healthcare workers facing increased exposure to the virus, increased workloads, and increased stress and burnout. The double burden of COVID-19 and cancer on the healthcare system has implications for policy and practice, including the need for improved coordination between cancer and COVID-19 response efforts and the need for increased investment in healthcare infrastructure and resources. In conclusion, the COVID-19 pandemic has created a double burden on the healthcare system, with significant challenges in the diagnosis and treatment of cancer. The impact of COVID-19 on healthcare workers and the healthcare system more broadly highlights the need for improved coordination and increased investment in healthcare resources and infrastructure.
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The concept of pharmaceutical care (PC) has existed as a professional philosophy for more than 30 years. However, for a long period of time, little had been done for its integration into the regular practice of healthcare provision. The COVID-19 pandemic and the resulting increase in patient influx in the community pharmacies (CP) encouraged the exploration and establishment of new healthcare services provided within the CP. Nevertheless, these services of PC are still novel, and more can be done to expand the community pharmacists' current role in primary healthcare. This can be achieved by improving and expanding the newly established services, all while incorporating new ones, for the benefit of public health and the reduction of avoidable healthcare expenditures. This article reviews information about the benefits of this service regarding patient health and the reduction of financial expenses pertinent to adverse drug events within the setting of the CP. Adverse drug events account for significant healthcare expenses and patient distress due to relevant symptoms, emergency doctor visits, and increased hospitalization rates. Several studies conducted internationally have investigated the positive impact of PC practiced by community pharmacists. In spite of results sometimes presenting a non-continuous pattern, PC applied under specific conditions has tangible positive outcomes. Congestive heart failure and type 2 diabetes mellitus patients presented fewer hospital admissions, better symptom control, and higher adherence in comparison to control groups, while a study on asthma patients revealed improved inhalation techniques. All intervention groups reported psychological improvement and a better understanding of their treatment. Special reference is made to the importance of this service for patients receiving anti-cancer treatment and how community pharmacists can have a crucial role in designing, monitoring, and re-designing these therapeutic schemes whose complexity and related adverse drug events negatively affect patient adherence. The role of community pharmacists was very important, especially for primary care, for both patients and healthcare systems during the pandemic, and it seems that it will remain decisive in the post-COVID era as well. The increased complexity of therapy and polypharmacy creates the need for organized, active participation of pharmacists in healthcare provision so that they can use their knowledge and skills under continuous cooperation with other healthcare professionals, thus providing coordinated services for the benefit of the patient.
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COVID-19 , Community Pharmacy Services , Diabetes Mellitus, Type 2 , Drug-Related Side Effects and Adverse Reactions , Pharmacies , Humans , Pandemics , COVID-19/epidemiology , Pharmacists/psychologyABSTRACT
BACKGROUND: Timely access to the operating room for emergency general surgery (EGS) indications remains a challenge across the globe, largely driven by operating room availability and staffing constraints. The "timing in acute care surgery" (TACS) classification was previously published to introduce a new tool to triage the timely and appropriate access of EGS patients to the operating room. However, the clinical and operational effectiveness of the TACS classification has not been investigated in subsequent validation studies. This study aimed to improve the TACS classification and provide further consensus around the appropriate use of the new TACS classification through a standardized Delphi approach with international experts. METHODS: This is a validation study of the new TACS by a selected international panel of experts using the Delphi method. The TACS questionnaire was designed as a web-based survey. The consensus agreement level was established to be ≥ 75%. The collective consensus agreement was defined as the sum of the percentage of the highest Likert scale levels (4-5) out of all participants. Surgical emergency diseases and correlated clinical scenarios were defined for each of the proposed classes. Subsequent rounds were carried out until a definitive level of consensus was reached. Frequencies and percentages were calculated to determine the degree of agreement for each surgical disease. RESULTS: Four polling rounds were carried out. The new TACS classification provides 6 colour-code classes correlated to a precise timing to surgery, defined scenarios and surgical condition. The WHITE colour-code class was introduced to rapidly (within a week) reschedule cancelled or postponed surgical procedures. Haemodynamic stability is the main tool to stratify patients for immediate surgery or not in the presence of sepsis/septic shock. Fifty-one surgical diseases were included in the different colour-code classes of priority. CONCLUSION: The new TACS classification is a comprehensive, simple, clear and reproducible triage system which can be used to assess the severity of the patient and the surgical disease, to reduce the time to access to the operating room, and to manage the emergency surgical patients within a "safe" timeframe. By including well-defined surgical diseases in the different colour-code classes of priority, validated through a Delphi consensus, the new TACS improves communication among surgeons, between surgeons and anaesthesiologists and decreases conflicts and waste and waiting time in accessing the operating room for emergency surgical patients.
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Surgeons , Triage , Humans , Delphi Technique , Triage/methods , Consensus , Operating RoomsABSTRACT
BACKGROUND: Despite considerable efforts to encourage telehealth use during the COVID-19 pandemic, we witnessed a potential widening of health inequities that may continue to plague the US health care system unless we mitigate modifiable risk factors. OBJECTIVE: This study aimed to examine the hypothesis that there are systemic differences in telehealth usage among people who live at or below 200% of the federal poverty level. Factors that we consider are age, gender, race, ethnicity, education, employment status, household size, and income. METHODS: A retrospective observational study was performed using the COVID-19 Research Database to analyze factors contributing to telehealth inequities. The study period ranged from March 2020 to April 2021. The Office Ally database provided US claims data from 100 million unique patients and 3.4 billion claims. The Analytics IQ PeopleCore Consumer database is nationally representative of 242.5 million US adults aged 19 years and older. We analyzed medical claims to investigate the influence of demographic and socioeconomic factors on telehealth usage among the low-income racial and ethnic minority populations. We conducted a multiple logistic regression analysis to determine the odds of patients in diverse groups using telehealth during the study period. RESULTS: Among 2,850,831 unique patients, nearly 60% of them were female, 75% of them had a high school education or less, 49% of them were unemployed, and 62% of them identified as non-Hispanic White. Our results suggest that 9.84% of the patients had ≥1 telehealth claims during the study period. Asian (odds ratio [OR] 1.569, 95% CI 1.528-1.611, P<.001) and Hispanic (OR 1.612, 95% CI 1.596-1.628, P<.001) patients were more likely to use telehealth than non-Hispanic White and -Black patients. Patients who were employed full-time were 15% (OR 1.148, 95% CI 1.133-1.164, P<.001) more likely to use telehealth than unemployed patients. Patients who identified as male were 12% (OR 0.875, 95% CI 0.867-0.883, P<.001) less likely to use telehealth than those who identified as female. Patients with high school education or less were 5% (OR 0.953, 95% CI 0.944-0.962, P<.001) less likely to use telehealth than those with a bachelor's degree or higher. Patients in the 18-44-year age group were 32% (OR 1.324, 95% CI 1.304-1.345, P<.001) more likely to use telehealth than those in the ≥65-year age group. CONCLUSIONS: Factors that impact telehealth usage include age, gender, race, education, employment status, and income. While low-income racial and ethnic minority communities are at greater risk for health inequities among this group, Hispanic communities are more likely to use telehealth, and non-Hispanic Black patients continue to demonstrate telehealth inequity. Gender, age, and household income contribute to health inequities across gradients of poverty. Strategies to improve health use should consider characteristics of subgroups, as people do not experience poverty equally.
Subject(s)
COVID-19 , Health Services Accessibility , Telemedicine , Adolescent , Adult , Aged , Female , Humans , Male , Young Adult , COVID-19/epidemiology , Hispanic or Latino , Pandemics , Poverty , United States/epidemiology , White , Black or African American , AsianABSTRACT
After starting in late 2019, COVID-19 spread worldwide, and Italy was one of the first Western nations to be seriously affected. At that time, both the virus and the disease were little known and there were no Evidence-Based Medicine indications for treatment. The Italian Health Ministry guidelines claimed that, unless oxygen saturation fell to <92%, no pharmacological treatment was necessary during the first 72 hours, other than on a purely symptomatic basis, preferably with paracetamol. As later confirmed, that delay in therapeutic intervention may have been responsible for numerous hospital admissions and a very high lethality (3.5 %). To try to remedy this situation, several volunteer groups were formed, managing to promptlycure thousands of patients at home with non-steroidal anti-inflammatory drugs and a variety of re-purposed drugs (principally hydroxychloroquine, ivermectin) and supplements (such as antioxidants, polyphenols and vitamin D). Although not documented by any randomized controlled studies, these approaches were nonetheless based on the best available evidence, were aimed at addressing otherwise unmet major needs and produced a significant reduction of hospitalizations, of symptom duration, and a complete recovery from the disease compared with late treatment, according to some retrospective observational studies and the clinical experience of many physicians. A prompt discussion, with a clear and open exchange between healthcare Institutions and the said groups of voluntary physicians, could clarify the most effective approaches to reduce the number of hospitalizations and the lethality of this disease.
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Introduction: After contracting COVID-19, many people have continued to experience various symptoms for several weeks and months, even after a mild acute phase. These people with `long COVID' faced difficulties when confronted with the healthcare system. Purpose of research: In order to better understand their experience, we supplemented the information obtained in an online survey with a mixed qualitative approach based on 33 individual interviews and discussions with 101 participants in a forum in March 2021. Results: Several shortcomings were identified in the contacts of `long' COVID patients with the health care system, such as the lack of listening or empathy of some health care professionals, the lack of a systematic or proactive approach during the diagnostic assessment, or the lack of interdisciplinary coordination. Patients feel misunderstood and are forced to develop their own strategies, whether for diagnosis or treatment. Patients' discomfort has led them to question the value of medicine and to resort to unconventional therapies to alleviate their symptoms, sometimes at great cost. Conclusions: Better informing the medical profession about the manifestation of the disease and the possible treatments, including the possibilities of reimbursement, would raise awareness and give them the tools to respond to the needs of ` long' COVID patients. A comprehensive assessment of the patient through an "interdisciplinary assessment" seems necessary.
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Biosensors using opto electronics mechanisms are evolving as efficient (sensitive and selective) and low-cost analytical diagnostic devices for early-stage disease diagnosis, which is crucial for person-centered health and wellness management. Due to advancements in nanotechnology in the areas of sensing unit fabrication, device integration, interfacing, packaging, and sensing performance at the point-of-care (POC), personalized diagnostics are now possible, allowing doctors to tailor tests to each patient's unique disease profile and management requirements. Innovative biosensing technology is being pushed as the diagnostic tool of the future because of its potential to provide accurate results without requiring intrusive procedures. Because of this, this visionary piece of writing explores analytical methods for managing personalised health care that IP 203.8 109.10 On: Th , 16 F b 2023 14 53 21 can enhance the health of the general population. The end goal is to take control of a healthier tomorrow as Copyright: Ame can Scientific Pub shers soon as possible. Right now, the most crucial part of controllig the COVID-19 pandemic, a potentially fatal Delive ed by Ingenta respiratory viral disease, is the rapid, specific, and sensitive detection of human beta severe acute respiratory system coronavirus (SARS-CoV-2) protein.
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In social IoMT systems, resource-constrained devices face the challenges of limited computation, bandwidth, and privacy in the deployment of deep learning models. Federated learning (FL) is one of the solutions to user privacy and provides distributed training among several local devices. In addition, it reduces the computation and bandwidth of transferring videos to the central server in camera-based IoMT devices. In this work, we design an edge-based federated framework for such devices. In contrast to traditional methods that drop the resource-constrained stragglers in a federated round, our system provides a methodology to incorporate them. We propose a new phase in the FL algorithm, known as split learning. The stragglers train collaboratively with the nearest edge node using split learning. We test the implementation using heterogeneous computing devices that extract vital signs from videos. The results show a reduction of 3.6 h in the training time of videos using the split learning phase with respect to the traditional approach. We also evaluate the performance of the devices and system with key parameters, CPU utilization, memory consumption, and data rate. Furthermore, we achieve 87.29% and 60.26% test accuracy at the nonstragglers and stragglers, respectively, with a global accuracy of 90.32% at the server. Therefore, FedCare provides a straggler-resistant federated method for a heterogeneous system for social IoMT devices.
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Health care and rescue system resilience is the multifactoral sum of technology, humans, information, processes, and management. The coronavirus (COVID-19) pandemic has been a catalyst for transformation globally and tested the resilience of health care and rescue systems in many ways. The relevant use of technology has been acknowledged as one important element in developing resilience, but there are still very few empirical studies that have studied the role of technology in supporting system-level resilience. This chapter examines how information system solutions have advanced system resilience during the COVID-19 crisis through a literature review and empirical case study of the Finnish health care and rescue sector. According to the results of this study, the use of different technology solutions and digital services in health care and rescue has increased during the pandemic, as the crisis has accelerated the development of an information system (IS) for data sharing as well as experiments on AI and robotics. However, in developing IS solutions, several challenges arise that are specific to the health care and rescue sector that need to be taken into account: strict legislation, the privacy of health data, and the fact that implementation of a digital service cannot compromise patient care. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Nigeria remains the largest economy in Africa. However, its health sector is described as weak. It continues to battle several challenges ranging from poor health infrastructure, inaccessibility of good quality health care, corruption, substandard drugs circulating, poor funding, shortage of healthcare personnel, high cost of healthcare amidst poverty-stricken masses, among others. The outbreak of Covid-19 and the global oil price crash have further impacted Nigeria's dwindling healthcare service delivery/ indicators. This chapter thus takes stock of the status of the healthcare indicators, healthcare systems, and healthcare governance in Nigeria before and during the Covid-19 pandemic to decipher the impact of the damage caused by Covid-19 on the already weak Nigeria's health sector. It discusses healthcare indicators, system constraints and responses, and the demand and supply of health care in Nigeria in the era of Covid-19. This chapter shows how Covid-19 has negatively and positively affected the healthcare sector in Nigeria. However, the negative impact remains overwhelming and has potentially grave consequences. This study thus develops a policy framework and time-tested strategy to recover Nigeria's health sector while factoring in the present capabilities of Nigeria's health sector. This study thus recommends that adequate infrastructure investment and welfare for healthcare workers are important for the recovery of Nigeria's health sector. © 2023 Kemi Ogunyemi and Adaora I. Onaga. All rights reserved.
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This paper presents a reflection on the experience of obtaining a PhD degree in Participatory Healthcare Systems amid the COVID-19 pandemic. The paper first introduces the PhD research and how the methodology was adjusted during the pandemic. Then, the reflections are presented considering the benefits/advantages (the good), the barriers/difficulties (the bad) and the struggles (the ugly). The topics presented show that positive aspects were overshadowed by the emotional burdens and increasing limitations of data collection and study design. Learnings from this experience indicate that designing a more resilient methodology that integrates creative methods, supporting PhD students to pause the research, fostering a culture of care that rethinks what a successful PhD is, and a greater focus on the Mental Health of PhD students is advisable. [ FROM AUTHOR] Copyright of Design for Health is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Coronavirus illness (COVID-19) had a major impact on multiple areas in society including the healthcare system and the downfall of the global economy. The researchers, doctors, and specialists are working towards new techniques to identify COVID-19 more quickly, such as developing a device that can detect the COVID-19 automatically. In this paper, we propose an automated detection mechanism for identifying COVID-19 patients using a patient's chest X-ray images. The proposed system made use of CNN (convolutional neural network) and an ensemble of a set of classifiers. The CNN is used for feature extraction in the training and input image whereas classifiers are used for effective prediction. Some of the binary ML (machine learning) classifiers are used for the identification of COVID-19 based on the retrieved characteristics. Later these results are grouped to create a pool of ensemble of classifiers to assure superior results considering various datasets of different sized images with varying resolutions. The performance analysis is discussed and shown as it is better than other previous schemes using deep learning, with 99.17 percent accuracy, 99.19 percent precision, 99.17 percent recall, and 99.43 percent F1 score. The system's high value in the automated detection of COVID-19 is maintained due to its quick identification and low false-negative rate. © 2022 IEEE.