Empirical Evaluation of Deep Learning Models with Local Binary Pattern for COVID-19 Detection

COVID-19 (Coronavirus Disease 2019) has impacted many lives globally. Though vaccines have been found recently, many people lose their lives due to lack of early detection of the disease. Deep learning has gained significant interest in detecting COVID-19 through the use of image modalities. Conventional works have also attempted to attain better outcome in COVID-19 detection. However, they need further improvement with respect to accuracy. Applying image processing steps on data set before the application of deep learning (DL) model seems to improve the performance. The objective of proposed research work is to enhance the performance of deep learning models by using image denoising and feature extraction. Performance of proposed Local binary pattern (LBP)-DL is tested against conventional DL Models and found to be more efficient and accurate in COVID-19 detection. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Evaluating Potential Delays and Outcomes of Patients Undergoing Surgical Resection for Locally Advanced and Recurrent Colorectal Cancer during a Pandemic

Aim: The COVID-19 pandemic resulted in a significant disruption of colorectal cancer (CRC) care pathways. This study evaluates the management and outcomes of patients with primary locally advanced or recurrent CRC during the pandemic in a single tertiary referral center. Method(s): Patients undergoing elective surgery for advanced or recurrent CRC with curative intent between March 2020 -March 2021 were identified. Following first MDT discussion patients were broadly classified into two groups: straight to surgery (n = 22, 45%) or neoadjuvant therapy followed by surgery (n = 27, 55%). Primary outcome was COVID-19 related complication rate. Result(s): 49 patients were included with a median age of 66 years (IQR:54-73). No patients developed a COVID-19 infection or related complication during hospital admission. Significant delays were identified in the treatment pathway of patients in straight to surgery group, mostly due to delays in referral from external centers. 9/22 in the straight to surgery group had evidence of tumour progression vs 3/27 in neoadjuvant group, (P = 0.015839). 7/27 in the neoadjuvant group showed evidence of tumour regression. During the study, surgical waiting times were reduced and more operations were performed during the second wave of COVID-19. Conclusion(s): This study suggests that it is possible to mitigate the risks of COVID-19 related complications in patients undergoing complex surgery for locally advanced and recurrent CRC. Delay in surgical intervention is associated with tumour progression, particularly in patients who may not have neoadjuvant therapy. Efforts should be made to prioritize resources for patients requiring time-sensitive surgery for advanced and recurrent CRC.

Real-Time Smart Attendance Monitoring System With Thermal Scanning

In conventional attendance system, taking roll call in class time or monitoring the presence of student/employee in an educational institute or an industry has been a time-consuming process. It is also very important to see that all educational institutes are concerned about the consistency of student's performance. The main cause of this is decrease is due to inadequate attendance. So, an advanced student attendance checking system is required which supports the faculty to keep records of attendance. In this project we have introduced an intelligent face recognition-based attendance system. We have proposed to implement a 'Smart Attendance through Face Recognition' which uses viola-jones algorithm for training and detection of faces. Because viola jones is highly strong, and its use has proved to be particularly noteworthy in real-time detection. The present implementation includes time-saving facial identification and eradicates the possibilities of proxy attendance due to facial authorization. In this pandemic season to alert the staff about the infected covid patients we are using thermal scanning to detect the temperature of a person. So that we would be the reason to decrease the spread of covid and save innocent lives. This system can now be used in an area in which participation plays an important role. © 2022 IEEE.

Evaluating potential delays and outcomes of patients undergoing surgical resection for locally advanced and recurrent colorectal cancer during a pandemic.

INTRODUCTION: The COVID-19 pandemic resulted in a significant disruption of colorectal cancer (CRC) care pathways. This study evaluates the management and outcomes of patients with primary locally advanced or recurrent CRC during the pandemic in a single tertiary referral centre. METHODS: Patients undergoing elective surgery for advanced or recurrent CRC with curative intent between March 2020 and March 2021 were identified. Following first multidisciplinary team discussion patients were broadly classified into two groups: straight to surgery (n=22, 45%) or neoadjuvant therapy followed by surgery (n=27, 55%). Primary outcome was COVID-19-related complication rate. RESULTS: Forty-nine patients with a median age of 66 years (interquartile range: 54-73) were included. No patients developed a COVID-19 infection or related complication during hospital admission. Significant delays were identified in the treatment pathway of patients in the straight to surgery group, mostly due to delays in referral from external centres. Nine of 22 patients in the straight to surgery group had evidence of tumour progression compared with 3 of 27 in the neoadjuvant group (p=0.015839). Seven of 27 patients in the neoadjuvant group showed evidence of tumour regression. During the study, surgical waiting times were reduced, and more operations were performed during the second wave of COVID-19. CONCLUSION: This study suggests that it is possible to mitigate the risks of COVID-19-related complications in patients undergoing complex surgery for locally advanced and recurrent CRC. Delay in surgical intervention is associated with tumour progression, particularly in patients who may not have neoadjuvant therapy. Efforts should be made to prioritise resources for patients requiring time-sensitive surgery for advanced and recurrent CRC.

A diagnostic host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease-19 (COVID-19), has emerged as the cause of a global pandemic. We used RNA sequencing to analyze 286 nasopharyngeal (NP) swab and 53 whole-blood (WB) samples from 333 patients with COVID-19 and controls. Overall, a muted immune response was observed in COVID-19 relative to other infections (influenza, other seasonal coronaviruses, and bacterial sepsis), with paradoxical down-regulation of several key differentially expressed genes. Hospitalized patients and outpatients exhibited up-regulation of interferon-associated pathways, although heightened and more robust inflammatory responses were observed in hospitalized patients with more clinically severe illness. Two-layer machine learning-based host classifiers consisting of complete (>1000 genes), medium (<100), and small (<20) gene biomarker panels identified COVID-19 disease with 85.1-86.5% accuracy when benchmarked using an independent test set. SARS-CoV-2 infection has a distinct biosignature that differs between NP swabs and WB and can be leveraged for COVID-19 diagnosis.

Magnitude and Kinetics of Anti-Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Responses and Their Relationship to Disease Severity.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can be detected indirectly by measuring the host immune response. For some viruses, antibody concentrations correlate with host protection and viral neutralization, but in rare cases, antiviral antibodies can promote disease progression. Elucidation of the kinetics and magnitude of the SARS-CoV-2 antibody response is essential to understand the pathogenesis of coronavirus disease 2019 (COVID-19) and identify potential therapeutic targets. METHODS: Sera (n = 533) from patients with real-time polymerase chain reaction-confirmed COVID-19 (n = 94 with acute infections and n = 59 convalescent patients) were tested using a high-throughput quantitative immunoglobulin M (IgM) and immunoglobulin G (IgG) assay that detects antibodies to the spike protein receptor binding domain and nucleocapsid protein. Individual and serial samples covered the time of initial diagnosis, during the disease course, and following recovery. We evaluated antibody kinetics and correlation between magnitude of the response and disease severity. RESULTS: Patterns of SARS-CoV-2 antibody production varied considerably. Among 52 patients with 3 or more serial specimens, 44 (84.6%) and 42 (80.8%) had observed IgM and IgG seroconversion at a median of 8 and 10 days, respectively. Compared to those with milder disease, peak measurements were significantly higher for patients admitted to the intensive care unit for all time intervals between 6 and 20 days for IgM, and all intervals after 5 days for IgG. CONCLUSIONS: High-sensitivity assays with a robust dynamic range provide a comprehensive picture of host antibody response to SARS-CoV-2. IgM and IgG responses were significantly higher in patients with severe than mild disease. These differences may affect strategies for seroprevalence studies, therapeutics, and vaccine development.

COVID-19 Transmission Risks Assessment using Agent-Based Weighted Clustering Approach

Coronavirus is a pandemic disease spreading from human-to-human rapidly all over the world. This virus is origin from common cold to severe disease such as MERS-CoV and SARS-CoV. Initially it was identified in China, December 2019. The main aim of this research is used to identify the COVID-19 transmission risks assessment from human-to-human within a cluster. The agent-based weighted clustering approach is used to identify the corona virus infected people rapidly within a cluster. In the weighted clustered approach, the normal agents are consisted as susceptible node and the corona virus infected people are considered as malicious node. The Cluster Head (CH) is elected based upon some weighting factors and the trust value is evaluated for all the agents within the cluster. The cluster head were periodically transfers the malicious node information to all other nodes within the cluster. Finally, the agent-based weighted clustering machine learning model approach is used to identify the number of corona virus infected people within the cluster. © 2020. All Rights Reserved.

SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood.

Given the limited availability of serological testing to date, the seroprevalence of SARS-CoV-2-specific antibodies in different populations has remained unclear. Here, we report very low SARS-CoV-2 seroprevalence in two San Francisco Bay Area populations. Seroreactivity was 0.26% in 387 hospitalized patients admitted for non-respiratory indications and 0.1% in 1,000 blood donors in early April 2020. We additionally describe the longitudinal dynamics of immunoglobulin-G (IgG), immunoglobulin-M (IgM), and in vitro neutralizing antibody titers in COVID-19 patients. The median time to seroconversion ranged from 10.3-11.0 days for these 3 assays. Neutralizing antibodies rose in tandem with immunoglobulin titers following symptom onset, and positive percent agreement between detection of IgG and neutralizing titers was >93%. These findings emphasize the importance of using highly accurate tests for surveillance studies in low-prevalence populations, and provide evidence that seroreactivity using SARS-CoV-2 anti-nucleocapsid protein IgG and anti-spike IgM assays are generally predictive of in vitro neutralizing capacity.

Evaluation of SARS-CoV-2 serology assays reveals a range of test performance.

Appropriate use and interpretation of serological tests for assessments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure, infection and potential immunity require accurate data on assay performance. We conducted a head-to-head evaluation of ten point-of-care-style lateral flow assays (LFAs) and two laboratory-based enzyme-linked immunosorbent assays to detect anti-SARS-CoV-2 IgM and IgG antibodies in 5-d time intervals from symptom onset and studied the specificity of each assay in pre-coronavirus disease 2019 specimens. The percent of seropositive individuals increased with time, peaking in the latest time interval tested (>20 d after symptom onset). Test specificity ranged from 84.3% to 100.0% and was predominantly affected by variability in IgM results. LFA specificity could be increased by considering weak bands as negative, but this decreased detection of antibodies (sensitivity) in a subset of SARS-CoV-2 real-time PCR-positive cases. Our results underline the importance of seropositivity threshold determination and reader training for reliable LFA deployment. Although there was no standout serological assay, four tests achieved more than 80% positivity at later time points tested and more than 95% specificity.

Magnitude and kinetics of anti-SARS-CoV-2 antibody responses and their relationship to disease severity (preprint)

Background: SARS-CoV-2 infection can be detected indirectly by measuring the host immune response. Anti-viral antibody concentrations generally correlate with host protection and viral neutralization, but in rare cases, antibodies can promote disease progression. Elucidation of the kinetics and magnitude of the SARS-CoV-2 antibody response is essential to understand the pathogenesis of COVID-19 and identify potential therapeutic targets. Methods: Sera (n=533) from patients with RT-PCR confirmed COVID-19 (n=153) were tested using a high-throughput quantitative IgM and IgG assay that detects antibodies to the spike protein receptor binding domain and nucleocapsid protein. Individual and serial samples covered the time of initial diagnosis, during the disease course, and following recovery. We evaluated antibody kinetics and correlation between magnitude of the response and disease severity. Results: Patterns of SARS-CoV-2 antibody production varied considerably. Among 52 patients with 3 or more serial specimens, 44 (84.6%) and 42 (80.8%) had observed IgM and IgG seroconversion at a median of 8 and 10 days, respectively. Compared to those with milder disease, peak measurements were significantly higher for patients admitted to the intensive care unit for all time intervals between 6 and 20 days for IgM, and all intervals after 5 days for IgG. Conclusions: High sensitivity assays with a robust dynamic range provide a comprehensive picture of host antibody response to SARS-CoV-2. IgM and IgG responses were significantly higher in patients with severe than mild disease. These differences may affect strategies for seroprevalence studies, therapeutics and vaccine development.

SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood from the San Francisco Bay Area (preprint)

We report very low SARS-CoV-2 seroprevalence in two San Francisco Bay Area populations. Seropositivity was 0.26% in 387 hospitalized patients admitted for non-respiratory indications and 0.1% in 1,000 blood donors. We additionally describe the longitudinal dynamics of immunoglobulin-G, immunoglobulin-M, and in vitro neutralizing antibody titers in COVID-19 patients. Neutralizing antibodies rise in tandem with immunoglobulin levels following symptom onset, exhibiting median time to seroconversion within one day of each other, and there is >93% positive percent agreement between detection of immunoglobulin-G and neutralizing titers.

Test performance evaluation of SARS-CoV-2 serological assays (preprint)

Background Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data. Method We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system. Results Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8-100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3-100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7-94.8%. No consistent cross-reactivity was observed. Conclusion Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies.