Mawidi: Smart Appointments Booking System for Social Distancing

In traditional systems of banks, the booking process requires the client to be in the same place, the client withdraws a numbered paper from an electronic device and then sits in the waiting area until his/her number appears on the screen. However, these systems may cause many problems such as wasting clients' time, overcrowding in the waiting area, slow workflow, etc. In this paper, a smart appointment booking system is developed to solve the problems of traditional booking systems of banks and achieve social distancing. The proposed system applies Quick Response (QR) code, Global Positioning System (GPS), and Bluetooth Low Energy (BLE) technologies to improve workflow and achieve social distancing in banks. The proposed system is developed on two sides. On the client-side, a mobile application is developed, a QR is generated for the user, which contains booking information, and GPS is used to determine the location of the client as it is only possible to book if he/she is within 100 meters from the bank. Due to the restrictions imposed caused by the spread of COVID-19, BLE technology works to ensure social distancing between clients. On the employee side, a website is created to enable the employee to deal with the client. The proposed system is expected to reduce problems related to traditional systems, gain client satisfaction, facilitate workflow for employees, and contribute to reduce the spread of COVID-19. © 2023 NSP Natural Sciences Publishing Cor.

Study epidemiology and determinants of COVID-19 infection among the population in Jeddah city, Saudi Arabia

Background: Coronavirus disease 2019 (COVID-19) is a global pandemic caused by a highly infectious respiratory virus (SARS-CoV-2). With all these consequences that threaten the health of the individual and society due to this infection, it has become necessary to have a vaccination that limits the spread of this virus. The objective of this study was to study the epidemiological aspects of COVID-19 pandemic in Jeddah, Saudi Arabia. Method: It was a cross sectional study of 405 subjects, who gave their responses through online Google form, as face to face interview of the subjects during outpatient clinic visits was not possible because of the pandemic of COVID-19 infection. Data was analyzed using SPSS software version 23. The level of significance was 0.05%. Results: The prevalence of Covid-19 infection was 23.7%. The vaccination coverage by the Covid-19 vaccine was 90.4%. Those who got the infection before getting the vaccine were 76%;on the other hand those who got the infection after getting one dose were 17.7% of the cases, while 6.3% got the infection after getting two doses of the vaccine. Those with autoimmune disorders, kidney failure and obesity were reluctant to get the vaccine (p <0.05). Married subjects, those with average income, and those who are employed were significantly more infected by COVID-19 (p<0.05). Patients with asthma, with autoimmune disorders, and those who did not take the COVID-19 vaccine, were significantly more vulnerable to COVID - 19 infection (p<0.05). Post vaccination clinical manifestations were mainly feeling tired (90.2%), pain and swelling at the site of injection (76.9%), fever (65.9%) and headache (61.8%%). Clinical manifestations associated with COVID-19 infection included fever (76.0%), headache (72.9%), loss of taste and smell (68.8%), body aches (67.7%), and sore throat (57.3%). Conclusions: Prevalence of COVID-19 infection was 23.7%. About one third of the population did not accept the vaccine. Subjects with asthma, autoimmune disorders, and those who were unvaccinated were more likely to catch the infection. Increasing the knowledge of the people about the clinical aspects, and health impact of the COVID-19 virus on the community are important intervention tools to increase the acceptance rate of COVID-19 vaccination among the population.

Correlation of Lactate Dehydrogenase Level with Severity of Disease and In-hospital Outcome in Individuals Diagnosed with COVID-19: A Retrospective Study

Introduction: The presence of tissue damage in the lungs, kidneys, heart, or other organs can be detected by monitoring the level of Lactate Dehydrogenase (LDH) in the blood and considered a reliable biomarker in early prediction of patients' prognosis. Aim: To determine extent of correlation between LDH level with the spectrum and in-hospital outcome of Coronavirus Disease -2019 (COVID-19) infected patients. Materials and Methods: This retrospective research was undertaken during March 2020 to May 2020, based on the data of 205 COVID-19 infected patients, reported at Dammam Medical Complex, Dammam, Eastern Province, Saudi Arabia. Patients' records were retrieved and the following data were recorded-age, gender, nationality, co-morbidities, lactate dehydrogenase level, number of days since the patient tested positive (Up to 7,14 and > 14 days), COVID-19 symptoms [mild, moderate, or severe as per British Thoracic Society guidelines (CURB (Confusion, Blood Urea Nitrogen, Respiratory Rate, Blood Pressure)-65)]. The data was collected and tabulated as mean +/- SD, frequency and percentages. Analysis was carried out using specialized software of Statistical Package for Social Sciences (SPSS) version 20.0. Results: On analysis of the collected data of all 205 included patients, the LDH level was found significantly high among males, 46-60 years old, and among non-Saudi patients. The severity of COVID-19 symptoms and LDH levels were found to have a strong relationship (p-value < 0.001). Patients between the ages of 46 and 60 were more likely (4.3 times) to have poor outcomes, and diabetes mellitus was predicted to be 2.32 times more likely to be associated with poor COVID-19 outcomes. Raised LDH levels were > 5 times more likely to lead to in-hospital poor outcomes compared to those with borderline LDH levels. Conclusion: LDH level is a reliable predictor for the cause of COVID-19. The results of the present study suggest that patients aged 46-60 years, diabetic patients, or those suffering from severe symptoms of COVID-19 have raised levels of LDH.

Enhancing deep learning techniques for the diagnosis of the novel coronavirus (COVID-19) using X-ray images

Deep learning techniques combined with radiological imaging provide precision in the diagnosis of diseases that can be utilised for the classification and diagnosis of several diseases in the medical sector. Several research studies have focused on binary classification of COVID-19, and there is limited research focusing on multiclass classification of COVID-19. The purpose of this study is to develop a model that can enhance the multiclass classification of COVID-19 using raw chest X-ray images. The study involved using convolutional neural networks as the classifier. Five pre-trained deep learning models including VGG16, MobileNet, EfficientNetB0, NasNetMobile and ResNet50V2 are used to distinguish between COVID-19 infection and other lung diseases. Data Augmentation and Normalization techniques have been used to improve the models' performance and avoid training problems. The study findings revealed that it is possible to distinguish between COVID-19 infection and other lung diseases using pre-trained deep learning models. The proposed technique successfully classifies five classes (normal, COVID-19, lung opacity, viral pneumonia, and bacterial pneumonia). It is found that NasNetMobile model outperformed the rest of the models and achieved the highest results. It achieved an overall accuracy, sensitivity, specificity and precision of 91%, 91%, 97.7% and 91%, respectively. The VGG16 model produced better results in detecting COVID-19 infection, resulting in an accuracy of 95.8%. The suggested technique is more accurate in comparison to the other newly developed techniques presented in the literature. This provides healthcare staff with a powerful tool for the diagnosis of COVID-19 based on deep learning. © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Incidence of Guillain-Barré Syndrome post COVID-19: a systematic review of case reports and case series.

OBJECTIVE: The purpose of this systematic review was to study the incidence, risk factors and patients subjected to Guillain-Barré syndrome (GBS) after COVID-19. MATERIALS AND METHODS: For qualitative assessment and assessing the methodological quality, the Cochrane Handbook for Systematic Reviews of Interventions and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) checklist were utilized. Data from PubMed, Cochrane, Embase, CINAHIL, Medline, ResearchGate, and Scopus were searched. The relevant studies involved patients with confirmed COVID-19 diagnosis by RT-PCR, and GBS diagnosis based on typical clinical symptoms and/or confirmatory diagnostic results. A total of 12 English relevant articles (6 papers were case reports and 8 were case series with a total of 32 patients) published in a peer-reviewed journal from 2019 to 2021 were included. Following the review methodology, two independent raters were responsible for retrieving, extracting and checking for data eligibility. Demographic characteristics are presented as frequencies and percentages. Based on distribution of values, continuous data were expressed as median and interquartile range (IQR). RESULTS: Out of 32 patients, 26 patients reported neurological symptoms, 6 cases went unnoticed, 7 cases showed involvement of the cranial nerves, 12 cases did not, and 13 cases went unreported. CONCLUSIONS: It is too early to draw any conclusions concerning a potential relationship between SARS-CoV-2 infection and GBS. More large-scale observational studies are required to understand the pathogenesis of SARS-CoV-2-associated GBS and to demonstrate a definite causal relationship between GBS and SARS-CoV-2 infection.

Post-COVID-19 non-traumatic iliopsoas hematoma: A case report

Background: Critically ill COVID-19 patients have an elevated risk of experiencing hypercoagulable conditions. Currently, many COVID-19 patients have been administered anticoagulation or antiplatelet therapies to lower the risk of systematic thrombosis. Iliopsoas hematoma is a potentially fatal and rare complication of bleeding disorders or anticoagulation therapy which sometimes grows to become clinically significant. The main purpose of this case review is to emphasize the importance of diagnosing iliopsoas hematomas and the possibility of antiplatelet contribution to its development. Case Presentation: We are reporting a rare presentation of non-traumatic iliopsoas hematoma in a non-anticoagulated patient. The patient is a 59-year-old male, with known type-2 diabetes, on oral hypoglycemic medications, 3-weeks post-COVID-19. He had started aspirin 81 mg orally, once daily, to prevent thrombotic events associated with COVID 19 infection, with no anticoagulant use and no other medications. He came in through the ED, presenting with two weeks history of progressive right lower limb weakness in which an iliopsoas hematoma diagnosis was confirmed based on radiological investigation. Conclusion: The possibility of iliopsoas hematoma should be considered in non-anticoagulated patients with no inherited or acquired coagulation disorders presenting with limb weakness. The link between antiplatelet use in a COVID-19 patient and the development of soft tissue bleeding (e.g., iliopsoas hematoma) must be studied further. © 2022 [The Author/The Authors]

Correlation of Lactate Dehydrogenase Level with Severity of Disease and In-hospital Outcome in Individuals Diagnosed with COVID-19: A Retrospective Study

Introduction: The presence of tissue damage in the lungs, kidneys, heart, or other organs can be detected by monitoring the level of Lactate Dehydrogenase (LDH) in the blood and considered a reliable biomarker in early prediction of patients' prognosis. Aim(s): To determine extent of correlation between LDH level with the spectrum and in-hospital outcome of Coronavirus Disease-2019 (COVID-19) infected patients. Material(s) and Method(s): This retrospective research was undertaken during March 2020 to May 2020, based on the data of 205 COVID-19 infected patients, reported at Dammam Medical Complex, Dammam, Eastern Province, Saudi Arabia. Patients' records were retrieved and the following data were recorded-age, gender, nationality, co-morbidities, lactate dehydrogenase level, number of days since the patient tested positive (Up to 7,14 and >14 days), COVID-19 symptoms [mild, moderate, or severe as per British Thoracic Society guidelines (CURB (Confusion, Blood Urea Nitrogen, Respiratory Rate, Blood Pressure)-65)]. The data was collected and tabulated as mean+/-SD, frequency and percentages. Analysis was carried out using specialized software of Statistical Package for Social Sciences (SPSS) version 20.0. Result(s): On analysis of the collected data of all 205 included patients, the LDH level was found significantly high among males, 46-60 years old, and among non-Saudi patients. The severity of COVID-19 symptoms and LDH levels were found to have a strong relationship (p-value<0.001). Patients between the ages of 46 and 60 were more likely (4.3 times) to have poor outcomes, and diabetes mellitus was predicted to be 2.32 times more likely to be associated with poor COVID-19 outcomes. Raised LDH levels were >5 times more likely to lead to in-hospital poor outcomes compared to those with borderline LDH levels. Conclusion(s): LDH level is a reliable predictor for the cause of COVID-19. The results of the present study suggest that patients aged 46-60 years, diabetic patients, or those suffering from severe symptoms of COVID-19 have raised levels of LDH. Copyright © 2023 Journal of Clinical and Diagnostic Research. All rights reserved.

Healthcare workers' preparedness and management to prevent adverse effects and social pain related to COVID-19

There is still a lack of information among scientists related to COVID-19. There were many side effects related to the COVID-19 infection and those side effects were both physical and psychological. Healthcare workers were a group of individuals who faced many issues regarding COVID-19. Their management was a key role in controlling those issues. This review paper has tried to collect the recent data with a focus on the management of healthcare workers in the prevention of adverse effects and social pain related to COVID-19. For this purpose, Scopus, Google Scholar, PubMed and Web of Science were used. The findings of this research confirmed the practical role of healthcare workers in the prevention of adverse effects and social pan related to COVID-19. Copyright © Nova Science Publishers, Inc.

The role of hospital staff in early prevention and detection of physical pain in COVID-19 situation

Occurrence of physical pain related to Coviv-19 is a common issue among affected individuals. This pain could have a negative effect on performance and quality of life among patients. Early detection would be a practical way to prevent from serious level of pain. This study has tried to collect the available data regarding this issue and emphasize the role of the hospital staff. For this purpose, Scopus, Google Scholar, Science Direct and Web of Science were used. The keywords were including COVID-19, pain, early detection, and hospital staff. The findings showed the important role of hospital staff in prevention and detection of pain related to COVID-19 among individuals. Copyright © 2022 Nova Science Publishers, Inc.

The Impact of Excessive Use of Digital Devices During the Pandemic of Corona Virus Disease (COVID-19) Among Saudi Arabia Population

Background: A substantial increase in using digital devices was observed among the population due to staying at home as a result of the quarantine during the coronavirus pandemic. Consequently, ocular symptoms appeared due to spending several hours of screen time per day. Objective(s): The current study aimed to assess the impact of excessive use of digital devices during the pandemic of coronavirus among the Saudi population. Method(s): A community-based cross-sectional study was carried out from November 2020 to January 2021 among the Saudi population. Data were collected by using Ocular Surface Disease Index (OSDI) questionnaires for the assessment of symptoms related to dry eye and their effect on vision. A logistic regression model was used to evaluate the association between the risk factors and the symptoms of dry eye. SPSS 22nd edition was used, any p-value <0.05 was considered significant. Result(s): Out of 1573 participants, 93.8% used mobile, 42.4% experienced uncomfortable sensitivity to the light. There were 49.15% of the participants who showed that none of the time they felt blurry vision, 54.8% did not report double vision, and 30.5% who felt a headache recently after quarantine. About 48% of the participants did not have any ocular symptoms, while 52% had dry eye symptoms (mild 22.3%, moderate 13.7%, and severe 15.9%). When the logistic regression model of risk factors associated with severe symptoms of dry eye was applied, wearing a contact lens was the most significant variable (p<0.0001). Conclusion(s): Dry eye symptoms increased during the quarantine, which indicated that the digital device users need to learn more about the preventive measures from practitioners in eye healthcare. More studies are warranted to assess the impact of digital device usage on all age groups starting from children up to the elderly population. Copyright © 2022 Almuhwwis et al.

An Exploration of Students and Lecturers’ Insights of Online University Learning Implemented During the COVID‐19 Contagion

The consequences of the coronavirus pandemic present serious threats to the normal functioning of the global economy, societies worldwide and specific institutions, including educational services. Confronting challenges arising from the fact that the changes needed to be enacted quickly, educational providers have resorted to online learning solutions via various platforms to limit the ongoing spread of COVID-19. To deepen knowledge and understanding of the critical benefits and difficulties that online learning has created during the pandemic, the present study investigates student and lecturer perceptions regarding the use and execution of online learning in higher education institutions. The sample is comprised of students and lecturers based in Al-Baha University, Saudi Arabia. The study unearths the major difficulties encountered in using online learning methods and identifies the key factors which have enabled more effective use of these methods. The study will use interviews to collect qualitative data on Al-Baha University students and lecturers’ insights and use thematic analysis to analyse and interpret the ensuing data. The resultant data and analyses will be used to formulate practitioner recommendations as to how online learning systems can be more effectively deployed throughout the pandemic and in future scenarios in which online learning becomes essential to education. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Differential impact of the angiotensin‑converting enzyme‑2 (ACE2 rs4343 G>A) and miR‑196a2 rs11614913 C>T gene alterations in COVID‑19 disease severity and mortality

The recent coronavirus outbreak from Wuhan China in late 2019 caused by severe acute respiratory syndrome coronavirus‑2 (SARS‑CoV‑2) resulted in a global pandemic of coronavirus‑19 disease (COVID‑19). Understating the underlying mechanism of the pathogenesis of coronavirus infection is important not only because it will help in accurate diagnosis and treatment of the infection but also in the production of effective vaccines. The infection begins when SARS‑CoV‑2 enters the cells through binding of its envelope glycoprotein to angiotensin‑converting enzyme2 (ACE2). Gene variations of ACE2 and microRNA (miR)‑196 are associated with viral infection and other diseases. The present study investigated the association of the ACE2 rs4343

SOCIAL MEDIA UTILIZATION AND ITS IMPACT ON MALE MEDICAL STUDENTS' LEARNING DURING COVID-19 PANDEMIC

To assess the patterns of social media uses and their impact on the learning of male medical students during the COVID-19 pandemic. A cross-sectional descriptive study was conducted from March to May 2020 at the College of Medicine, University of Bisha (UBCOM) in Saudi Arabia. A validated questionnaire was used to collect data from the students at first year, pre-clerkship and clerkship levels about the types, patterns and benefits of social media usage in their learning. A five-Likert scale was used to measure the students' responses. Descriptive statistics and ANOVA tests were used for data analysis. Of the 203 students enrolled, 89.2% (n=181) were responded. Most students commonly used Twitter (75.1%), followed by YouTube (52.5%) and Facebook (24.3%). The highest usage of Twitter was found among clerkship students (85.1%) compared to first-year (76.2%) and pre-clerkship students (69.6%), with no significant differences (p = 0.133). About 38.7% of students spent over 10 hours per week on social media and pre-clerkship students being the highest group (43.5%). Most students (67.9%) showed that social media enhance learning activities, 65.2% are interested in using social media in their learning and 64.1% suggested that their inappropriate use consumes time. We concluded social media become interactive tools of learning in medical schools during the urgent situation such as the COVID-19 pandemic. Such findings highlighted the benefits of considering social media inclusion when designing medical curricula.

RDPVR: Random Data Partitioning with Voting Rule for Machine Learning from Class-Imbalanced Datasets

Since most classifiers are biased toward the dominant class, class imbalance is a challenging problem in machine learning. The most popular approaches to solving this problem include oversampling minority examples and undersampling majority examples. Oversampling may increase the probability of overfitting, whereas undersampling eliminates examples that may be crucial to the learning process. We present a linear time resampling method based on random data partitioning and a majority voting rule to address both concerns, where an imbalanced dataset is partitioned into a number of small subdatasets, each of which must be class balanced. After that, a specific classifier is trained for each subdataset, and the final classification result is established by applying the majority voting rule to the results of all of the trained models. We compared the performance of the proposed method to some of the most well-known oversampling and undersampling methods, employing a range of classifiers, on 33 benchmark machine learning class-imbalanced datasets. The classification results produced by the classifiers employed on the generated data by the proposed method were comparable to most of the resampling methods tested, with the exception of SMOTEFUNA, which is an oversampling method that increases the probability of overfitting. The proposed method produced results that were comparable to the Easy Ensemble (EE) undersampling method. As a result, for solving the challenge of machine learning from class-imbalanced datasets, we advocate using either EE or our method.

Saudi adherence to preventive measures from COVID-19;a survey to assess preventive practices as a basis for general community health education

Introduction: Preventive behaviour is vital to the success of any intervention in the control of the COVID-19 pandemic addressing community health. Objectives: To answer the extent to which the Saudi Population is aware and complies with the preventive measures of COVID-19, and to identify the associated factors. Methodology: This is a descriptive, community-based survey of the Saudi Population. The data was collected using a self-administered questionnaire that included respondent characteristics, and questions about the preventive behaviour towards COVID-19. The IRB of the University of Bisha, College of Medicine gave the ethical clearance. Result: A total of 1200 people participated in the online survey. Females were 607 (50.6%) and 593 (49.4%) were males. The majority of the Saudi Population had adequate knowledge of COVID-19 preventive measures (71.4%), adherence to preventive measures of COVID-19 was (47.5%). Factors associated with adequate adherence to the preventive measures of COVID-19 were age, occupation, education level, previous suspicion of COVID-19, and contact with infected persons, and a risk factor (p-value <0.05). Adherence to preventive measures as a daily routine practice was significantly associated with age, residence, occupation, suspected COVID-19, and previous infection (p-value <0.05). Conclusion: Although most of the Saudi Population has adequate knowledge of COVID-19 preventive measures, adherence to preventive measures was low. Therefore, we recommend increasing the awareness and compliance of the people to the preventive measures of COVID-19. © 2021, Medical Project Poland. All rights reserved.

Healthcare workers’ preparedness and management to prevent adverse effects and social pain related to COVID-19

There is still a lack of information among scientists related to COVID-19. There were many side effects related to the COVID-19 infection and those side effects were both physical and psychological. Healthcare workers were a group of individuals who faced many issues regarding COVID-19. Their management was a key role in controlling those issues. This review paper has tried to collect the recent data with a focus on the management of healthcare workers in the prevention of adverse effects and social pain related to COVID-19. For this purpose, Scopus, Google Scholar, PubMed and Web of Science were used. The findings of this research confirmed the practical role of healthcare workers in the prevention of adverse effects and social pan related to COVID-19.

Perception of first-year medical students of virtual video demonstration of the objective structured clinical examination at king saud university medical college in saudi arabia during the covid-19 pandemic

Background: The coronavirus disease of 2019 (COVID-19) has challenged and disrupted medical education worldwide. Objective structured clinical examination (OSCE) is one of the types of assessment for undergraduate medical students that has been conducted for first-year medical students in the College of Medicine. Peer student training on participating in OSCE has been conducted prior to the pandemic. The aim of this study was to assess medical students’ perception of online virtual peer student video training on participating in the OSCE. Methods: Medical student’s council team prepared a video demonstration on the steps of participating in OSCE. In October 2020, the video was provided online for first-year medical students (n = 302) prior to their OSCE. After the completion of the OSCE exam, a 10 – item questionnaire was distributed on the students’ perception on the impact of the peer student video demonstration on students’ orientation about the OSCE. The questionnaire was sent by Google Forms. The results were expressed as a percentage on a Likert scale. Results: About 74.17% (n = 224) of students responded to the online questionnaire. More than half of the students (n = 126, 56%) found the steps of conduction of the OSCE well explained, provided the sufficient orientation (n = 121, 54%), and found the video stimulating (n = 122, 54%). In addition, the majority of students (n = 160, 71%) learned and understood the steps of the OSCE and 152 students (68%) found that the video helped introducing them to the concept of OSCE. Almost half the students found that the video helped lowering the stress level before the OSCE (n = 91, 41%), eased the steps of the OSCE (n = 113, 50%), and found that the materials were well prepared and explained (n = 126, 56%). Conclusions: The virtual video demonstration of the OSCE during the COVID-19 pandemic had an overall positive perception from first-year medical students. However, peer student’s orientation on the OSCE will continue after the pandemic. Further supports for first-year medical students are needed during the pandemic. © 2021 Journal of Nature and Science of Medicine.

The Effect of Change People Lifestyle in Saudi Community during COVID-19 Quarantine on Increasing Number of Chronic Neck Pain Cases

Background: The Chronic Neck Pain is the process of degeneration of the cervical spine and the vertebral bodies. It affects the vertebral bodies and intervertebral disks of the neck and finally leads to herniation of the disks as well as osteophytes and ligament hypertrophy. Purpose: The cross-sectional analytical study focused on the effect of people Lifestyle during COVID-19 quarantine on number of cases of Musculoskeletal Disorders (MSD) especially Non-Specific Chronic Neck Pain in Jeddah (Saudi Arabia), and compare number of cases before and after the quarantine with taking into account the difference in age and gender. COVID-19 period was characterized by lockdown and quarantine. Methods: data collected from one hospital in Jeddah according the patients diagnosed by Non-Specific Chronic Neck Pain in between (1 August 2019 to 30 September 2020) male and female, age 28- 40, exclusion criteria: patient with history of fracture in cervical spine, cervical tumors, neck trauma, patient with age more than 40 and less than 28. Collecting the data of 7 months before the quarantine and 7 months during the quarantine. Results: After collecting and counting data, we noticed that there was a doubling in the number of cases and neck problems, and an increase in the number of cases during quarantine by (58.6%), while in females by (46.25%) in general. It increased by 53.3% of cases. Conclusion: The results clearly showed that the effect of people's lifestyle during the quarantine of the emerging corona virus, COVID-19, on the number of cases of Musculoskeletal Disorders (MSD), especially chronic non-specific neck pain in Jeddah (Saudi Arabia), and its impact on males more than females.

A Systematic Review: Role of Artificial Intelligence During the COVID-19 Pandemic in the Healthcare System

Certainty, artificial intelligence (AI) has a remarkable role in the control of the COVID-19 pandemic globally. This review article aimed to determine the outcomes/benefits associated with the use of artificial intelligence during the COVID-19 pandemic in different specialties in healthcare. Out of 144 articles, 100 publish article abstracts were reviewed using keywords artificial intelligence, intelligent health systems during COVID-19 pandemic, medical education. This review determined that artificial intelligence has a significant role in predicting the spread of disease by chasing the infected population and can prove as a powerful tool for public health professionals. There is a remarkable role of AI-assisted diagnostic features in radiology to specifically diagnose infected cases with COVID-19. AI assists in taking quicker decision making among health professionals through AI operated apps.This review highlights the need for future research which should emphasize determining the effectiveness and challenges of the use of robotics during pandemics.