Impact of COVID-19 on Delivery of Cancer Care: Real-World Insights from Community Oncology Research Evaluations (CORE)

Objectives: The COVID-19 pandemic has disrupted healthcare delivery for patients with cancer. This research assessed the impact of COVID-19 on the delivery of cancer care in the US during the pandemic and evaluated emerging treatment trends in the post-COVID-19 setting. Method(s): A series of Community Oncology Research Evaluations (CORE) meetings were conducted across the US between December 2021 and May 2022. During these meetings, community oncologists undertook a survey focused on the impact of COVID-19 in the community-practice setting. Result(s): 242 community oncologists participated in the survey. Over 80% of the physicians estimated that up to 20% of patients with cancer have gone undiagnosed due to their reluctance to visit a healthcare provider during the pandemic. More than half (51%) of community oncologists reported a decrease of up to 50% in in-office patient visits versus before COVID-19, with most physicians (71%) indicating that some delivery of care changed to a virtual setting in up to 20% of patients. Most physicians (86%) reported no change in their willingness to assess new therapies. Most common strategies to manage cancer during the pandemic included the use of telemedicine for stable patients receiving oral chemotherapy (55%), use of extended dosing schedules (39%), and switching route of chemotherapy administration from intravenous to oral or subcutaneous (38%). Once COVID-19 is under control, these strategies are expected to remain in place. Nearly half of the community oncologists (48%) plan to continue using telemedicine for managing disease in stable patients receiving oral chemotherapy, over a quarter intend to continue using extended dosing schedules, and 19% plan to use oral or subcutaneous chemotherapy when appropriate. Conclusion(s): COVID-19 had a detrimental impact on cancer diagnosis and delivery of therapy. Community oncologists reported a seemingly permanent shift in care patterns including telemedicine, extended dosing schedules, and switching chemotherapy administration route.Copyright © 2023

Experimental (FT-Raman, FT-IR and NMR) and theoretical (DFT) calculations, thermodynamic parameters, molecular docking and NLO (non-linear optical) properties of N-(2,6-dimethylphenyl)-1-piperazineacetamide

Theoretical and experimental studies are performed on the new organic-inorganic hybrid molecule N-(2,6-dimethylphenyl)-1-piperazineacetamide. The vibrational spectra of the molecule are characterized using FT-IR and FT-Raman in the range 4000-600 cm(-1) and 4000-100 cm(-1), respectively. Density functional theory with B3LYP/3-21G and B3LYP/cc-pVDZ basis sets is used to calculate energy, geometrical structure, and vibrational modes of stretching, bending, and torsion. The VEDA software Autodock Vina revealed a good binding is employed to calculate the detailed vibrational assignments. The theoretical and experimental vibrational data are compared to support the present study. Density functional theory is used to calculate thermodynamic parameters (heat capacity, entropy, and enthalpy) and nonlinear optical properties. The software Gaussian09W and Gaussview 6.0 are used for theoretical calculations. Molecular docking studies are carried out to investigate the effect of the titled molecule against various proteins such as SARS-CoV-2 that affect the immune system in humans. Chemical shifts are identified using carbon and proton NMR. Non-covalent interactions are studied using a reduced density gradient. The chemical reactivity and selectivity for a local reactivity site are analyzed with the help of Fukui functions.

Histomorphological Spectrum of Lung Lesions at Autopsy-A Tertiary Care Centre Experience

Background and aims: A wide variety of pathological conditions involve the lungs. In autopsy, the lungs are examined for disease, injury and other findings suggesting cause of death or related changes.Aims & Objectives: The present study aimed to study the histomorphological spectrum of lung lesions at autopsy and to assess the frequency of different types of lesions;and to associate histomorphological changes with cause of death.Material and Methods: It was a one-year observational study conducted in the Department of Pathology, Govt. Medical College, Jammu. Lung tissue pieces from all medicolegal autopsies received were fixed, examined grossly, processed;paraffin embedded sections obtained were stained with Hematoxylin and Eosin stain and examined under microscope. Findings were recorded and tabulated. Result(s): Out of 264 cases, males were predominantly affected (84%);median age was 38 years. The various changes observed were congestion (68%), edema (45.4%), pneumonia (5%), granulomatous inflammation (3%), diffuse alveolar damage (1.5%), haemorrhage (14.4%), interstitial changes (60%), malaria (0.4%) and malignancy (0.4%). Natural deaths were the commonest cause (75, 28%) followed by asphyxial deaths (65, 24.6%). Conclusion(s): Histopathological examination of lung autopsies highlights many incidental findings, establishes underlying cause of death, serves as a learning tool and also holds scope for detection of newer diseases.Copyright © 2023 JK Science.

COVID-19: Insights into Structure-Function Relationship, Drug Targets and Drug Design Strategies for Novel-Coronavirus 2019

Background: Novel coronavirus (2019-nCov) imposed deadly health calamity with unexpected disastrous situation alarming the globe for urgent treatment regimes. World Health Organization (WHO) termed the coronavirus disease as COVID-2019 on February 11, 2020 and announced its outbreak as pandemic on 11 March 2020. The first infection was noticed in Wuhan, Hubei province, China, in December 2019, and it is believed that the corona-virus is transmitted to humans through bats as a reservoir involving human to human transfer. However, the proper intermediary transmission channel is yet to be unestablished. Method(s): Elderly populations and patients with concomitant symptoms are more at risk as compared to middle-aged patients as it may progress to pneumonia followed by severe acute respiratory syndrome (SARS) and multi-organ failure. Morbidity rates estimated in patients are less, i.e., 2-3%, but the dearth of a specific treatment strategy to prevent coronavirus infection is a major concern. Result(s): Currently, anti-viral and anti-malarial drugs are in practice for the management of COVID-19 disease along with plasma therapy in the absence of a potent vaccine. Besides, home isolation and social distancing are the precautionary measures adopted by many countries to minimize the spread of infection. Various studies have been conducted, and numerous are still going on to establish specific treatment for COVID-19. Conclusion(s): In this review, we summarized information on the structural components of COVID19 virus with special emphasis on the virus genome, life cycle, the importance of protease enzyme, the role of spike proteins in viral replication, validated drug targets, ongoing effective treatments for COVID-19 management and the latest research on drug design to develop anti-CoV drugs.Copyright © 2021 Bentham Science Publishers.

Privacy Preserving Based Personal Health Records Sharing Using Rail Fence Data Encryption (RFDE) for Secure Cloud Environment

The development of cloud technology is a fundamental idea for offering unfettered access to many different sources in the planning of the networking, memory, infrastructure, and software. Computers are becoming more and more widespread across a wide range of industries due to their numerous advantages, notably in the healthcare industry. Typically, it is essential to the interchange of health information. In light of the ongoing issues with password security, sending private medical information via the internet still raises serious privacy concerns. Whether or whether they have complete permission, patients are not forced to divulge any of their private or personal information. This article examines several noteworthy recent studies that address the problems of password security and data privacy for cloud-based health services. These compare the benefits and drawbacks of different physical access preservation techniques. The paper also proposes a combined authentication procedure based on RFDE models. Cloud security is usually greatly hampered by the necessity for information privacy in an effort to protect sensitive and non-sensitive data for decision-making and to solve the problem of information leakage. One of the most challenging parts of the transfer of personal health records (PHRs) to the cloud is the reuse and exchange of accurate, complete medical evidence. When PHRs are outsourced to third-party businesses, such as cloud services, they are often used as patient-centered, private ways of exchanging health information. Data about a particular PHR doctor is coded for protection before being sent to the cloud. However, there are still substantial barriers due to issues with security, things that can be improved, lawful consumer privacy portfolio management, efficiency, and regulation over sensitive and non-sensitive data kept in the cloud. The PHR file may be encrypted using the Rail Fence Data Encryption (RFDE) technique to provide strong confidentiality rules and enable PHR and modular connectivity control to perform at their very best. Unauthorized users are managed to stop from accessing information with the aid of the transposition cypher, also used by RFDE and known as 'zigzag encryption.' The recommended technique generates the secret key while encrypting the PHR information. The recipient decrypts the PHR data using the private key. The algorithm works brilliantly in comparison to the prior strategy. © 2022 IEEE.

Application of machine learning approaches to predict the impact of ambient air pollution on outpatient visits for acute respiratory infections

With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 1:2, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R2 = 0.606, 0.608 without lag and 1-day lag respectively on ARI patients and R2 = 0.872, 0.871 without lag and 1-day lag respectively on total patients. All eight models did not perform well with the lag effect on the ARI patient dataset but performed better on the total patient dataset. Thus, the study did not find any significant association between ARI patients and ambient air pollution due to the intermittent availability of data during the COVID-19 period. This study gives insight into developing machine learning programs for risk prediction that can be used to predict analytics for several other diseases apart from ARI, such as heart disease and other respiratory diseases. © 2022 Elsevier B.V.

Exploring the boundaries of Neuromarketing through systematic investigation

Neuromarketing literature has grown remarkably in recent years. Although the field has generated a diverse body of knowledge, we still find a dearth of studies classifying the existing literature into research themes and further presenting known and unknown aspects of Neuromarketing from a business and management viewpoint. To bridge this gap, the present study conducted a systematic literature review of Neuromarketing from 2011 to 2021, with a sample of 100 peer-reviewed articles. Based on rigorous review and thematic analysis of 41 relevant research articles, four research themes were identified - 1) Phenomenon, 2) Application, 3) Bright side, and 4) Dark side of Neuromarketing. Further, a theoretical framework of neuromarketing effect on consumer behaviour was presented. Future research thrust areas in theory, application, methodology, and evidence were identified.

A radical change in the dental education model in the COVID-19 pandemic

The present cross-sectional, observational study was done to assess the new norms of dental education, its effect on the students, and awareness in the post-COVID-19 era. Every question had 2 options- after complete lockdown and after partial lockdown. A higher percentage of the students believed that quarantine during the lockdown enhanced their collaboration with their fellow students. 60.7 % of the students during the complete lockdown and 76.9% during the partial lockdown, felt more motivated by the distant technology-dependent model of education. Students during the complete lockdown (69.20%) and partial lockdown (69.50%) felt that online group discussion and discussion of clinical-based case scenarios had an enhancing effect on their learning. Dental students (67%) in the complete lockdown and 75.70% in the partial lockdown felt comfortable with the e-learning. During the complete lockdown, 57.9% of the subjects were not confident in the clinical skills acquired, whereas during the partial lockdown only 38.2% were not confident in the clinical skills acquired. Mean scores for dental education, clinical readiness, and self-preparedness were higher after the partial lockdown as compared to the complete lockdown. However, the self - preparedness was more after the partial lockdown as compared to the complete lockdown. Dental colleges have to deal with e-learning methods being developed all of a sudden due to the pandemic. However, there are still problems with online learning and teaching that can be improved with the help of a supportive administration and tutors recording of learning videos as well as proper training of the staff and students. © The Author(s), 2022.

Using modified DECAF Score in mortality prediction in acute exacerbation of COPD patients presenting to emergency department in a tertiary care hospital

Background: Chronic obstructive pulmonary disease (COPD) is a prominent cause of illness and mortality on a global scale. In 2019, it was predicted to rank as the sixth largest cause of mortality. COPD is one of the most prevalent non-communicable illnesses in the field of pulmonology. The DECAF score (Dyspnea, Eosinopenia, Consolidation, Acidemia, and Atrial Fibrillation) is a risk stratification tool for patients with AECOPD that can be used at the bedside to guide treatment, such as hospital at home for low-risk patients. The purpose of this study is to predict the in-hospital mortality in acute exacerbation of COPD patients with modified DECAF scores. Modified DECAF score includes Dyspnea, Eosinopenia, Consolidation, Acidemia and Frequency of Hospitalization. Material(s) and Method(s): A total of 50 patients attending Emergency Medicine Department with Acute Exacerbation of COPD were recruited to this hospital based observational study. This study was conducted at the Department of Emergency medicine & Pulmonary medicine, at APOLLO GLENEAGLES HOSPITALS, Kolkata. Result(s): COPD was more prevalent in the age groups of 41-50 years (28%) and 61-70 years (28%) followed by those having age between 51-60 years (22%). Majority of the COPD patients were males (88%) compared to (12%) females. Majority of the COPD patients were males (88%) compared to (12%) females. Most common co-morbid condition associated with COPD washypertension (16%) followed by IHD (8%), pulmonary hypertension (6%) and diabetes mellitus (4%). Out of 50 patients with COPD, 11 (22%) had previous history of AECOPD, 38 (76%) were regular user of inhaler, 33 (66%) had history of influenza vaccination, 16 (32%) had Pneumococcal Vaccination and 2 (4%) patients had COVID-19 pneumonia. Out of 50 patients, 24 (48%) had Dyspnea (eMRCD) score of 5a whereas 26 (52%) had Dyspnea (eMRCD) score of 5b as well as 7 (14%) had Eosinopenia (<50 cells/mm3) and 20 (40%) had Consolidation. Conclusion(s): We conclude that the Modified DECAF score is both sensitive and specific in predicting in-hospital mortality in AECOPD patients. Modified DECAF is a simple tool that predicts mortality that incorporates routinely available indices. It effectively stratifies COPD patients admitted with acute exacerbations into mortality risk categories. Copyright © 2022 Ubiquity Press. All rights reserved.

Microbial aerosols generation during various dental procedures in an university hospital

Background: Aerosols generated during dental procedures carry potential hazardous microorganisms which may harm the patients and the health care worker attending the clinics. Though the risk of aerosol generating procedures had been already in place but has been highlighted after the pandemic of SARS-Cov-2 has setup.

Telemedicine - A way forward for medical consultation at high altitude

The recent advances in telemedicine have offered real and practical opportunities to health-care providers in sharing expertise and resources in health care over distances. In India, telemedicine has revolutionized the health-care system by minimizing the cost, avoiding the long-distance travels and in timely providing specialist care in remote areas. The Indian Army is also reaping the benefits of telemedicine, by providing round-the-clock medical care to the troops deployed in high-altitude areas.

The art of gamifying digital gig workers: a theoretical assessment of evaluating engagement and motivation

The COVID-19 global pandemic has transformed work and employment patterns within organizations. Two key emerging trends visible at the organization level are as follows. First, employees being asked to leave (which has mostly been seen within the aviation, hospitality, and travel industries) and second, employees asking to work part-time or on a contractual basis (e.g. within the education and healthcare sectors). This so-called ‘new normal’ has also given rise to an unprecedented increase and diffusion of digital workforces being engaged either full or part time within organizations. Thus, through our study, we aimed to contribute from a theoretical standpoint by exploring this phenomenon through the lenses of swift trust theory (STT) and psychological contract theory (PCT). Our goal was to understand how firms use gamification to engage their digital gig workforce. We collected our data from organizations that used some form of gamification in the process of engaging their employees and extended our inquiry to understand whether they did the same in engaging their gig workforces. We restricted our data to only those firms that had engaged white-collar gig workers. Overall, our study contributes to the literature by extending the theoretical debate pertaining to the use of STT and PCT theory to understand the phenomenon of digital gig workforce engagement and productivity. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Knowledge, Awareness And Practice Of Dental Practitioners Regarding COVID-19 Pandemic- A Cross-Sectional Study

Background: The present study was conducted to assess knowledge, awareness and practice of dental practitioners regarding COVID-19 pandemic. Materials & Methods: 240 dental practitioners of both genders were provided with a questionnaire regarding knowledge and practice regarding COVID-19 pandemic. Results: 80% showed that SARS-CoV-2 is the cause of COVID- 19. 85% replied that 2-14 days is the incubation period of Covid- 19, 75% correctly replied that 6.8 % is the incubation period for COVID- 19 and 82% replied that rRT-PCR is the laboratory test available for detection of COVID- 19. 80% replied yes in order to provide treatment to infected patients and 10% replied no. In response to question whether masks, head cap and sanitizer protect against virus, 74% replied yes, 18% replied no and 8% replied don’t know. The difference was significant (P< 0.05). Conclusion: Dental practitioners had sufficient knowledge, awareness and practice regarding COVID-19 pandemic.

A Decentralized Digital Voting System Based on Block chain Architecture

Voting is the backbone of democracy and the fundamental right of every citizen. BlockChain based Election is like a boon for every nation through which the election can be conducted digitally, Unlike those old (paper based) and traditional (EVM) voting systems it makes the whole process of election safe, smooth and easy. In this era of Covid-19 this Block chain enabled election is the need of the hour, People can cast votes from their own space just with the help of a mobile phone or a computer, Security would get enhanced and threats like EVM hacking, Chaos at election booth would reduce drastically just by the implementation of this advanced voting system. Personal ID's and unique keys would be provided to each and every eligible voter which can't be tampered at any cost. It has two modules to make the entire project look consolidated and unified. First module is the Election Commission who could be liable for undertaking it, appending concerned everyone competing for the voting attached under blockchain. User end will be the resident's component where every eligible voter can choose a leader according to their separate Constituent sitting and the votes would get registered on the blockchain to make it tamper protected. © 2022 IEEE.

COVID-19 Outbreak: A Paradigm Shift in Food and Beverage Industry with Context to Delhi-NCR

Almost all types of businesses are facing the challenge of global spread COVID-19 outbreak, but the food and beverage industry (including both offline and online meal chains) has been severely affected by this pandemic effect. This world-class issue has brought down the GDP and economic growth of the country. The pandemic issue has increased the restaurant’s expenses by creating pressure to expend more over the sanitation and hygiene factors. So, all these problems that the food and beverage industry are facing nowadays due to the corona pandemic inspired the researcher to work on this topic. The researcher has collected the data from particularly Delhi-NCR region by taking four constraints—consumer behavior, hygiene and safety measures, customer satisfaction. To test the hypothetical assumption of this descriptive study, the researcher has implied chi-square test, KMO test and Bartlett’s test, etc. The data analysis results showed that customer satisfaction is affected by all the variables used in this study and also identified that almost all of the customers considered hygiene as a vital variable out of all, which affects their dining choices and preferences. So, the rationale of this study can help the restaurants in adopting suitable safety measures to attract and satisfy their customers again. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Digital AI in hematology-integration of the scopio labs x100 scanner with newly implemented AI capabilities into routine clinical work flow

BACKGROUND Digital pathology and artificial intelligence (AI) are areas of growing interest in pathology. A number of institutes have already integrated digital imaging into routine workflow, relying on AI algorithms for the detection of various cancers and mitotic activity quantification. Despite the use of whole slide imaging (WSI) for tissue evaluation, the field of hematology has lagged behind. While many hospitals rely on limited technologies for automated peripheral blood evaluation (e.g. CellavisionTM), the Scopio LabsTM X100 digital scanner provides high resolution oil-immersion level dynamic images of large scanned areas (https://scopiolabs.com/hematology/). With recent FDA-clearance and newly implemented AI capabilities, the Scopio Labs scanner allows for clear and accurate cytomorphologic characterization and cell quantification for peripheral blood smears (PBS). To this end, we aimed to be one of the few pioneering institutes in the United States to adopt early and implement this technology into our routine workflow as a 'hub and spoke' model for optimized case assessment, data sharing and result reporting across multiple satellite locations within our hospital health system. DESIGN A Scopio x100 digital scanner was deployed at our main hospital site, with an anticipated secondary scanner for installment at a satellite laboratory. PBS flagged for hematopathologist review from two satellite laboratories were scanned, and full-field digitalized slides were evaluated by hematopathologists following AI automated analyses. RESULTS 311 peripheral smears were scanned since April 2021 and representative slides were digitalized at 100x magnification (Figure 1, weblink: https://demo.scopiolabs.com/#/view-scan/9231acaf-f898-4649-950d-a41c26c2baaa) with rapid monolayer, monolayer, fullfield, and full-field cytopenia scan options available. The automated AI capabilities classified cells into lineage-specific categories with quantification based on cytomorphologic features (Figure 2). Other AI features include additional cell assignment, cell annotation and comments accessible to all users, finalized report PDF generation, export, upload into our current PowerPath TM software with linkage to the corresponding flow cytometry and bone marrow biopsy reports;and the ability to share digitalized slides with clinicians, laboratory personnel and trainees using uniquely generated weblinks. Images can be used for lectures and tumor boards. Additionally, an 80-case study set for PBS was created for medical students, residents and fellow teaching purposes, including cases displaying acute B-cell lymphoblastic leukemia (B-ALL), acute myelomonocytic leukemia (AMML), hypersegmented neutrophils in COVID-19(+) patients, myelodysplastic syndrome (MDS), atypical lymphocytes, hemoglobinopathies, platelet disorders and various lymphomas. Overall improvements were made to the following areas: CLINICAL WORK/DIAGNOSIS 1. Time-saving due to pre-categorization of cells into lineage-specific groups for pathologist review 2. Minimizes subjectivity in cell counting and cellularity assessment EDUCATION 1. Case-based collection with flow and molecular being maintained here 2. Efficient case retrieval with retained annotations/comments for teaching purposes 3. Wide array of digitalized images for hematology atlas and publications ARCHIVING 1. Collection of reference images (intra/inter departmental) for an array of morphological entities for clinical reference and refined diagnosis (e.g. Bethesda reference images for pap by ASC) 2. Digital catalogue for long-term case follow-up and retrospective review CONCLUSION The Scopio Labs X100 digital system provides an efficient and cost-effective web-based tool to streamline clinical workflow and enhance PBS evaluation. With its recent AI capabilities of cell quantification, lineage-assignment and report-generation, we aim to continue our efforts to fully integrate Scopio Labs into our routine daily clinical workflow for reviewing PBS specimens. CONFLICT OF INTEREST STATEMENT The authors have nothing to isclose with regard to the submitted work (Figure Presented).

Pulmonary Illness Detection Early Warning System

Chronic Obstructive Pulmonary Disease is the 2nd most common genesis of Non-Communicable Diseases (NCD)-related deaths in India. Not everyone had the chance to go to a medical facility or hospital for problems/diseases other than COVID-19 amidst lockdown as there was uncertainty of getting infected by COVID-19. To cater this issue this device/software can detect and diagnose diseases such as pneumonia, heart failure, chronic obstructive pulmonary disease (COPD), emphysema, asthma, bronchitis, foreign body in the lungs or airways etc. This process uses methodology of signal, sound and audio processing and image analysis. Normal sound samples of healthy human body would be taken in consideration and then be compared with the samples of the person whom it is tested on, different levels or frequency range of sounds/body noises that a person makes differs in different analysis, for example 'crackles' these are high pitched breath sounds made when the small air sacs get liquid filled and the person may have pneumonia or a heart failure. This not only work as a warning system that is early but also can reduce human workload and can deplete human error while using a stethoscope for the same. © 2021 IEEE.

Global Prediction of COVID-19 Cases and Deaths using Machine Learning

Coronavirus Disease or COVID-19 pandemic has taken over the world by storm. It has horrifying effect on the health of the people. Continuously rising number of COVID-19 cases has and still creating huge stress on the governing bodies of all countries, and they are finding it hard to find solution for the situation. This project's goal is to explore machine learning and develop a COVID-19 model that can predict number of cases with high accuracy. The proposed study employs SVR and PR models to forecast the number of recovered cases, confirmed cases, deaths, and daily case count. The data is collected from the 1st of March to the 30th of April 2020. The confirmed number of cases as of April 30th were 35043, with 1147 total deaths and 8889 recovered patients. The model was created in Python 3.8.5. We will look at various machine learning prediction algorithms and compare them. In conclusion, supervised learning algorithms proved to be better than unsupervised learning algorithms. These prediction models can help us to brace for another COVID-19 wave and to ensure the availability of the required resources. © 2021 IEEE.

Grand Challenges in Bio-Nanotechnology to Manage the COVID-19 Pandemic

The outbreak of the COVID-19, a human beta coronavirus severe acute respiratory syndrome (SARS-CoV-2) virus infection, has severely affected the world. The pandemic is not yet in full control due to a lack of rapid diagnostics and therapeutics. This viral infection continues to result in a steadily increasing loss of life, and it has also emerged as a significant global socio-economic burden. As result, it has united many countries for the purposes of exploring molecular biology, biomedical science, and the nanotechnology to manage COVID-19 successfully. As of today, the current priority is to investigate novel therapies of high efficacy and smart diagnostics tools for early-stage disease diagnostics along with monitoring. Keeping these advancement and challenges in mind, this perspective article mainly highlights the contribution and possibilities of bio-nanotechnology to manage the COVID-19 pandemic, even in a personalized manner. Authors also pinpoint barriers to the utilization of current bio-nanotechnology to facilitate a more accurate understanding of COVID-19 and to lead the way toward personalized health and wellness. Furthermore, we follow the discussion of the features and challenges in upcoming bio-nanotechnology approaches for COVID-19 management. In this progressive option report, bio-nanotechnologies that have been enriched with the power of artificial intelligence and optimized at the personalized level have been found to lead to a sustainable treatment and cure strategy at a global population scale. Copyright © 2020 Paliwal, Sargolzaei, Bhardwaj, Bhardwaj, Dixit and Kaushik.

Comparing the Accuracy and the Efficiency in Detection of Coronavirus in CT Scans and X Ray Images

The Coronavirus pandemic, also known as the Covid pandemic, is a global disease (Coronavirus) pandemic caused by SARS Covid 2019 that causes severe respiratory illness (SARS-CoV-2). Side effects differ incredibly in seriousness, going from subtle to perilous. Individuals who are old or have basic clinical issues are more inclined to foster serious infection. Coronavirus is spread by means of the air when beads and small airborne particles dirty it. In this project we would be analyzing the data set images of Chest CT Scans and Chest X Rays for the Detection of Corona Virus using the different kind of deep learning algorithms and checking the efficiency of both of them as to which is more accurate and beneficial for detection of the corona virus pandemics so that this study can be used for future detection of COVID in the patients. © 2022, Springer Nature Switzerland AG.