COVID-19 Detection by Using Handcrafted Features Extracted From Chest CT-Scan Images

Coronavirus illness, which was initially diagnosed in 2019 but has propagated rapidly across the globe, has led to increased fatalities. According to professional physicians who examined chest CT scans, COVID-19 behaves differently than various viral cases of pneumonia. Even though the illness only recently emerged, a number of research investigations have been performed wherein the progression of the disease impacts mostly on the lungs are identified using thoracic CT scans. In this work, automated identification of COVID-19 is used by using machine learning classifier trained on more than 1000+ lung CT Scan images. As a result, immediate diagnosis of COVID-19, which is very much necessary in the opinion of healthcare specialists, is feasible. To improve detection accuracy, the feature extraction method are applied on regions of interests. Feature extraction approaches, including Discrete Wavelet Transform (DWT), Grey Level Cooccurrence Matrix (GLCM), Grey Level Run Length Matrix (GLRLM), and Grey-Level Size Zone Matrix (GLSZM) algorithms are used. Then the classification by using Support Vector Machines (SVM) is used. The classification accuracy is assessed by using precision, specificity, accuracy, sensitivity and F-score measures. Among all feature extraction methods, the GLCM approach has given the optimum classification accuracy of 95.6%. . © 2023 IEEE.

Investigation of Health Misinformation During the Covid-19 Pandemic

This study examines how misinformation related to Covid-19 on social media exacerbates individuals' perceptions of health threats. Informed by the Health Belief Model, we analyze over 5K fact-checked articles to identify different categories or topics of misinformation. We also analyze the veracity and temporal trends of the misinformation topics. Overall, thirteen topics emerged from our analysis, with most of the misinformation questioning the benefits of preventive actions and undermining the severity of the pandemic. We also found significant misinformation related to official sources such as health agencies and research institutes communicating about the pandemic. The findings have implications for social media and health research. Public health experts and policymakers might find insights helpful in designing better communication and intervention strategies to counter the false narrative about the pandemic. The study lays the ground to examine further motivations, mechanisms, and impacts of sharing health misinformation on social media. © 2023 IEEE Computer Society. All rights reserved.

Synthesis of new 3-(4-methyl-2-arylthiazol-5-yl)-5-aryl-1,2,4-oxadiazole derivatives as potential cytotoxic and antimicrobial agents

Globally cancer is the second leading cause of death;a drug that can cure cancer with the utmost negligible side effects is still a distant goal. Due to increasing antibiotic resistance, microbial infection remains a grave global health security threat. The ongoing coronavirus pandemic increased the risk of microbial and fungal infection. A new series of 3-(4-methyl-2-arylthiazol-5-yl)-5-aryl-1,2,4-oxadiazole (7a-t) have been synthesized. The structure of synthesized compounds was confirmed by the spectrometric analysis. The newly synthesized compounds were screened for cytotoxic activity against breast cell lines MCF-7 and MDA-MB-231. Against the MCF-7 cell line compounds 7f, 7 g and 7n showed excellent activity with GI50 0.6 muM to <100 nM concentration. Compound 7b showed good activity against MDA-MB-231 cell line with GI50 47 muM. The active derivatives 7b, 7e, 7f, 7 g and 7n were further evaluated for cytotoxicity against the epithelial cell line derived from the human embryonic kidney (HEK 293) and were found nontoxic. The thiazolyl-1,2,4-oxadiazole derivatives were also screened to evaluate theirs in vitro antimicrobial potential against Escherichia coli (NCIM 2574), Proteus mirabilis (NCIM 2388), Bacillus subtilis (NCIM 2063), Staphylococcus albus (NCIM 2178), Candida albicans (NCIM 3100) and Aspergillus niger (ATCC 504). Amongst the 7a-t derivatives, six compounds 7a, 7d, 7f, 7n, 7o, 7r showed good antifungal activity against C. albicans and eight compounds 7c, 7d, 7 g, 7h, 7i, 7k, 7l and 7o showed good activity against A. niger. The potential cytotoxic and antifungal activity suggested that the thiazolyl-1,2,4-oxadiazole derivatives could assist in the development of lead compounds for the treatment of cancer and microbial infections.Copyright © 2022 The Authors

A Covid-19 Tracker for Medical Front-liners

The management of Covid-19 affected patients is a very difficult task. The current healthcare system of India is not able to cope with the enormous flow of patients and is in a dire need for improvement. This implementation paper provides a system which will manage all the affected patients right from the time they are Covid-19 positive till the time they are treated and discharged. This paper includes all the technical details of a fully implemented healthcare management system which is a significant improvement in the current system. The proposed system is a cross platform multi user web app which can be used by multiple stakeholders to carry out smooth management of the patients. It consists of a lot of key features like dynamic location-wise patient status, an accurate tracking system of ambulances, a statistical trend analysis of patients and categorical report generation of patients. This system aims to help the medical Front-liners in efficient management of Covid-19 patients, and it is a common site for all the different health workers like field workers and medical officers to work togetherand fight against this deadly disease affecting our country. © 2022 IEEE.

REMICARE—Medicine Intake Tracker and Healthcare Assistant

An automated reminder mechanism is built in this Android-based application. It emphasizes the contact between doctors and patients. Patients can set a reminder to remind them when it is time to take their medicine. Multiple medications and timings, including date, time, and medicine description, can be programmed into the reminder by using image processing. Patients will be notified through a message within the system, as preferred by the patients. They have the option of looking for a doctor for assistance. In this COVID-19 pandemic situation where nurses have to remind the patients in the hospitals to take their medications, our application can be useful, alerting the patient every time of the day when he/she has to take the medicine and in what amounts. Also, all the necessary tests report and prescriptions can be saved on the cloud for later use. Patients will be provided with doctor contact information based on their availability. Also, patients will be notified of the expiry date of the medicine, and the former history of the medicines can be stored for further reference. The proposed system prioritizes a good user interface and easy navigation. Image processing will be accurate and efficient with the help of powerful CNN-RNN-CTC algorithm. It also emphasizes on a secure storage of the user's data with the help of the RSA algorithm for encryption and the gravitational search algorithm for secure cloud access. We attempted to create a Medical Reminder System that is cost-effective, time-saving, and promotes medication adherence. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Synthesis, antimicrobial and ergosterol biosynthesis inhibition activity of clubbed 1,1'-biphenyl-pyrazole derivatives

Microbial infections remain a grave threat to global health security due to the increase in antibiotic resistance. The ongoing coronavirus pandemic has increased the risk of microbial and fungal infections. New therapeutic agents are needed to combat microbial infections. Two series of new clubbed 1,1'-biphenyl-pyrazole have been synthesized. The newly synthesized pyrazole derivatives were evaluated for in vitro antibacterial activity against E. coli (NCIM 2574), P. mirabilis (NCIM 2388), B. subtilis (NCIM 2063), S. albus (NCIM 2178), and in vitro antifungal activity against A. niger (ATCC 504) and C. albicans (NCIM 3100). Compound 10b has shown good activity against P. mirabilis with MIC of 15.62 µg mL-1. Against C. albicans, eleven pyrazole derivatives 5c, 5e, 5f, 5g, 6a, 6b, 6c, 6e, 10b, 10c, and 11a have shown good antifungal activity with MIC of 62.5-31.25 µg mL-1. Also, against A. niger, seven compounds 5f, 5g, 6e, 10a, 10b, 10c, and 11b, have exhibited good activity with MIC of 62.5-31.25 µg mL-1. Compounds 6e, 10c, and 11b were further evaluated and showed ergosterol biosynthesis inhibition activity. Thus, the significant antimicrobial activity of 1-(3-substituted-4'-alkoxy-3'-(methylsulfonyl)-[1,1'-biphenyl]-4-yl)-5-substituted-3-(trifluoromethyl)-1H-pyrazole, and 1-isobutyl-5-(4'-alkoxy-3'-(methylsulfonyl)-[1,1'-biphenyl]-4-yl)-3-(fluoromethyl)-1H-pyrazole derivatives indicate that these compounds could assist in the development of lead compounds to treat microbial infections. © 2023 The Royal Society of Chemistry.

Real-Time Detection of Face Mask and Social Distancing

According to the World Health Organization data, the global epidemic of COVID-19 has profoundly affected the world and has now infected more than eight million people worldwide. The COVID-19 epidemic forced governments worldwide to close their doors to prevent the spread of the virus. Reports indicate that wearing a facemask and maintaining public distance while at work reduces the risk of infection. CCTV cameras are installed in educational and industrial spaces, residential areas, and crowded places. However, it is difficult to physically monitor buildings to find people without masks and people who do not keep public distance, and it is challenging to monitor video footage of large buildings and find people without a facemask and social distance correction. A mixed model that uses in-depth reading and machine learning to face masks and correct public distances will help managers look after people roaming the grounds without hiding their faces and distance from the public. The supervised machine-learning algorithm will train the model with the data available online. The facemask data acquisition set contains masked and non-masked images. OpenCV will be used for real-time face recognition and social distance adjustment from live streaming videos from web-enabled videos. The Convolution Neural Network will be used to extract features from the database. After the feature removal process, the newly installed photo/video will be classified as face masked or face masked. The proposed methodology has shown that person detection, social distance, and F.I. scores approximate 91.2%, and the average F1 score is 90.79%. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Graft injury and neutrophil lymphocyte ratio predicts the severity and survival due to COVID 19 among liver transplant recipients - Multicentre results from apcolis-lt study

Background: Liver Transplant recipients have an increased susceptibility to SARS CoV2 infection with a possible more severe disease course. There is paucity of data of SARSCoV2 infection in this cohort from Asia. We report on the data of an on-going APCOLIS-1 (APASL Liver Injury Spectrum, APCOLIS) registry with the aim to define the profile, risk factors for severity and predictors of survival among the liver transplant recipients. Methods: In a multinational study, data was recorded between April 2020 to May 2021 across 13 countries in Asia. The data was compiled on a survey monkey under the APASL COVID-19 study task force [NCT04345640]. We performed multivariate logistic regression to identify independent predictors of severity and all cause mortality among the liver transplant (LT) recipients suffering from COVID-19. Results: Altogether, 130 LT recipients were enrolled [mean age 53 ± 12 years, median post-transplant period, 54 months (range 2-77 months)]. Majority (92, 71% ) of the patients had undergone live-donor transplant. Severe COVID was seen in 21/130 (16%) and 17/130 (13%) required ICU care. COVID related organ failures (OF) were seen in 17 patients (13%), predominantly as respiratory (16/21, 76.2%) followed by renal (9/21, 42.8%) and circulatory (5/21, 23.8%) with ventilatory requirement in 12/21 (57.1%) of the severe cases. Among the baseline parameters age [HR=1.08, 95CI 1.01-1.16, p=0.03], presentation with dyspnea [HR=6.34, 95CI 1.78-22.9, p=0.004] and Neutrophil to Lymphocyte ratio (NLR) [HR=1.08, 95CI 1.01-1.17, p=0.04] independently predicted a severe course of the COVID-19 among LT recipients. The baseline NLR of 8.47 ± 1.45 peaked to 17.94 ± 3.68 in median of 15 days (range 1-37) among severe cases [p<0.001] indicating rapid progression of disease. Age above 55 years increased the disease severity with AUROC of 0.78, sensitivity of 72.7% and specificity of 74.8%. Time from LT, immunosuppression dosage or presence of co-morbidities did not influence the outcome. Graft dysfunction was seen in 21/130 (16%);predominantly as acute cellular rejection in 13/130 (10%) and graft failure 7/130 (5%). The all cause mortality was 8% (11/130). Among non-survivors, the baseline NLR of 4.88 ± 1.63 increased to a peak value of 25.14 ± 5.49 [p<0.001] i.e 5 folds. The baseline NLR [HR=1.17, 95CI 1.03-1.34, p=0.02], development of graft injury [HR=27.21, 95CI 2.55-290., p=0.006] and COVID related OF [ HR=21.87, 95CI 2.39-203.85, p=0.007] independently predicted mortality due to SARSCoV2 infection. Conclusion: COVID-19 infection precipitates a severe disease course in one fifth of the liver transplant recipients, leading to graft dysfunction and early mortality. LT recipients above 55 years of age, presenting with dyspnea and high NLR need to be specifically watched for a progressive disease course. Dynamic NLR determination can help in early stratification and referral to a specialized liver unit to improve outcomes.

Profile of sars cov2 infection among liver transplant recipients across asia pacific

Background: COVID-19 among liver transplant (LT) recipients varies with symptoms, severity, time from LT and with treatment from region to region. Here-with we report the clinical presentation, spectrum of disease and outcome from the Asia Pacific region. Methods: In this multinational study, data was recorded between April 2020 to May 2021 across 13 countries in Asia. The data was compiled on survey monkey under the APASL COVID-19 study task force [NCT04345640]. Severity of COVID infection was defined as per WHO guidelines. We analysed symptoms, demography, treatment, clinical course and treatment among LT patients with COVID-19. Results: Among a total 130 LT patients, males were 117 with mean age of 53±12 years and majority were live donor transplant (92,71%). The most common etiology of liver disease was ethanol (37, 28%) followed by NASH (28,22%) and cryptogenic(21,16%). Median post LT period was 54 months. Co-morbidity was present in 101 patients (78%), the most common being obesity (61,47%),followed by Diabetes (56,43%) and hypertension(30,23%). The presenting complaints were fever(82%), cough(61%), dyspnoea(29%) and diarrhoea(7%);8% were asymptomatic. Respiratory distress was seen in 29 (22%) cases;17 received only oxygen and 12 needed ventilator support. Prior to illness, only CNI was used as immunosuppressant in 30% (39), CNI & MMF in 31% (40) and in another 31% (40) mTOR inhibitors alone or with a CNI and triple regimen in 9%. During COVID, only low dose steroid was used in 50% (64), low dose CNI in mild to moderate ( 32%,41), complete avoidance of MMF in 4% cases where as low dose CNI and MMF in 16% (20) patients. Immunosuppression reintroduction done in 68% to pre-COVID dose and 28% were maintained on low dose CNI with steroids with close monitoring of LFT and pre-COVID dose was restarted after 14 days of recovery .4% had graft dysfunction leading to early augmentation of immunosuppression. Any antiviral was received by 36%, convalescent plasma by 26% and immunomodulators like tocilizumab or bevacizumab in 13%. Home care offered to 46% cases while those admitted, 41% were managed in ward only and 13% needed ICU admission. Graft function was unaffected in majority (109, 84%) but Acute Cellular Rejection was noted in 10% cases and DILI or other causes in 6%. Liver injury in the form of raised transaminases or bilirubin was noted in 19% at hospital stay and in 40% at presentation. Severe COVID was in 16% (21) cases with mortality in 8% (11). Conclusion: Compared to general population post-LT patients have an increased mortality due to COVID. Home based care could be feasible in only half of the patients.

Fact Check Using Multinomial Naive Bayes

An easy access to social media platforms has made information available effortlessly and thus has increased the intricacies to distinguish between true and falsified information. The credibility or reliability on social media platforms is also at stake. It is of utmost necessary to address this as a severe issue and act on it promptly. The extensive spread of counterfeit news has the potential for creating negative impacts on vast audience. Therefore, fake news detection on social media has become a very critical agenda in today’s world. This paper proposes a prototype to detect whether a news is fake or real using the multinomial Naive Bayes algorithm and its various architectures. Furthermore, the proposed prototype is capable of handling the unstructured data as the news can be in the form of images. In addition to this, the use of Django which is a high-level Python framework that allows the development of UI very easily with multiple designing options. As there was a high need of a 24/7 working server, the system has been deployed on Amazon Web Services EC2 Server as it gave less downtime and is highly reliable. Experimentation was done on the synthetic COVID news dataset created by collecting COVID news on social platforms. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Adopting a modified Delphi technique for revisiting the curriculum: a useful approach during the COVID-19 pandemic

Purpose The purpose of this paper is to describe a participatory qualitative research project using the Delphi consensus technique aided by Internet technology for successful transition of academic endeavors during and the post COVID era. The study aimed to derive a holistic competency matrix for an optometry program for transformation of the program to competency-based education. Design/methodology/approach This study combined a scoping review of literature for developing a baseline competency framework, along with derivation of an E-Delphi consensus within a panel of diverse stakeholders to achieve the objective of plotting a detailed competency matrix. Findings The involvement of all stakeholders of educational system in Delphi study resulted in a valid and all-inclusive competency framework with 18 competency units and 97 competency elements. This framework provided a strong base for redesigning pedagogy and assessment methods during COVID-19 crisis. Practical implications The paper highlights the feasibility and utility of adopting a participatory approach during COVID-19 outbreak. The Delphi technique aided by Internet technology was employed to develop a competency-based curriculum. Social implications The paper narrates a suitable, feasible and scientific method for rapid transition in academia, following the restrictions and social distancing norms imposed during the COVID-19 outbreak. Originality/value Although there is good evidence for use of the Delphi technique in curriculum development, this paper adds value by focusing on a participatory approach in using it. The suggested method here shows ways to gain optimum scientific output with minimum resources in constrained situations such as COVID-19 crisis.

The pandemic of 21st century - COVID-19

BACKGROUND The global pandemic of novel coronavirus disease is mainly caused by the infection of Coronavirus 'SARS-CoV-2'. It is infecting persons of all ethnicity, race and community. Corona viruses are enveloped RNA viruses which range from 60 to 140 nm in diameter with spike like projections on their top. Coronavirus is affecting 199 countries, territories and international transport systems. Covid-19 is a recent pandemic, which started in Wuhan, China, at the end of 2019 and now it is affecting the whole world. WHO declared this outbreak as a pandemic on March 11, 2020. COVID-19 infection is transmitted by inhalation or contact with infected droplets or aerosols of infected persons, and the incubation period ranges from 5 to 14 days. Viral aerosols remain active for 3 hours in the air, 24 hours on cardboards, and 2 to 3 days on stainless steel and plastic. Symptoms are usually fever, cough, breathlessness, sore throat, malaise and fatigue. In some people, it may progress to pneumonia, multiple organ dysfunction, and acute respiratory distress syndrome. People with heart diseases, lung diseases, cancer, old age, diabetics, Immunosuppressed, and pregnant women are at higher risk for COVID-19 infection. To date, there are now more than 2,732,701 cases of COVID 19 globally with more than 191,150 deaths. In India, total cases are 23,502 with 722 deaths. First case of coronavirus was seen on 29 January 2020. On 24 March 2020, the government of India under Prime Minister Shri Narendra Modi ordered a nationwide lockdown for 21 days, after a 14-hour voluntary public curfew on 22nd March. India is one of the most populous countries of the world. India has the second largest population in the world. Due to the lack of vaccines, ventilators, targeted therapies, mass gatherings, the Indian government started lockdown, the largest exercise in the world with the second largest population. To reduce public movement, section 144 was implemented in many states. A full lockdown will help the collapse of the whole national health system.

The great awakening-digitalization in dental healthcare during the pandemic covid19

Coronavirus disease in 2019, also called COVID-19, which has been widely spread worldwide had given rise to a pandemic situation. The public health emergency of international concern declared the agent as the (SARS-CoV-2) the severe acute respiratory syndrome and the World Health Organization had activated significant surveillance to prevent the spread of this infection across the world. Taking into the account about the rigorousness of COVID-19, and in the spark of the enormous dedication of several dental associations, it is essential to be enlightened with the recommendations to supervise dental patients and prevent any deprivement of education to the dental graduates due to insti-tutional closure. One of the approaching expertise that combines technology, communications and health care facilities are to refine patient care, it’s at the cutting edge of the present technological switch in medicine and applied sci-ences. Dentistry has been improved by cloud technology which has refined and implemented various methods to upgrade electronic health record sys-tem, educational projects, social network and patient communication. Technology has immensely saved the world. Economically and has created an insti-tutional task force to uplift the health care service during the COVID 19 pandemic crisis. Hence, the pandemic has struck an awakening of the practice of informatics in a health care facility which should be implemented and updated at the highest priority.