Deep Learning-Based COVID-19 Detection Using Transfer Learning Through ResNet-50

Catering to the widespread COVID-19 pandemic, the authors aim to develop a system based on machine learning combined with the knowledge of medical science. Considering the prevailing situation, it becomes necessary to diagnose the COVID-19 at initial stages. The idea behind the described designed model is to identify the spread of infection in patients as fast as possible. The paper sketches two different approaches: K-fold cross-validation and deep network designer which are based on deep learning technology for the prediction of COVID-19 in the initial stages by using the chest X-rays. The performance evaluation of the cross-fold validation process is compared with the designed application in the deep network designer to find an effective and efficient methodology for classification which attained better accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

LSTM-Based Prediction of COVID-19 Vaccination Drive in India

The vaccination drive for the much dangerous and contagious Coronavirus (COVID-19) has started successfully in India. This paper proposes to predict the vaccination drive of COVID-19 using the time series data for India. The proposed model was used for predicting the number of people to be vaccinated once per day in the country. The proposed model was compared with the direct input-based Long Short Term Memory (LSTM) cell model using various performance parameters and the proposed model was found to perform better. The actual closeness of the model's prediction from the actual data was depicted through line graphs. The proposed model was further used to predict the short-term and long-term future values. Herd immunity is another key ongoing research area when it comes to COVID-19. The Herd Immunity Threshold (HIT) of COVID-19 has not been found yet. However, this paper has proposed the expected number of days for different population thresholds. The proposed model predicts 174 days for obtaining a population threshold of 50% and 319 days for obtaining a population threshold of 90%. © 2021 IEEE.

Evolving oncology provider perspectives on care delivery during the COVID-19 pandemic

Background: The COVID-19 pandemic prompted rapid changes in cancer care delivery. We sought to examine oncology provider perspectives on clinical decisions and care delivery during the pandemic and to compare provider views early versus late in the pandemic. Methods: We invited oncology providers, including attendings, trainees and advanced practice providers, to complete a cross-sectional online survey using a variety of outreach methods including social media (Twitter), email contacts, word of mouth and provider list-serves. We surveyed providers at two time points during the pandemic when the number of COVID-19 cases was rising in the United States, early (March 2020) and late (January 2021). The survey responses were analyzed using descriptive statistics and Chisquared tests to evaluate differences in early versus late provider responses. Results: A total of 132 providers completed the survey and most were white (n = 73/132, 55%) and younger than 49 years (n = 88/132, 67%). Respondents were attendings in medical, surgical or radiation oncology (n = 61/132, 46%), advanced practice providers (n = 48/132, 36%) and oncology fellows (n = 16/132, 12%) who predominantly practiced in an academic medical center (n = 120/132, 91%). The majority of providers agreed patients with cancer are at higher risk than other patients to be affected by COVID-19 (n = 121/132, 92%). However, there was a significant difference in the proportion of early versus late providers who thought delays in cancer care were needed. Early in the pandemic, providers were more likely to recommend delays in curative surgery or radiation for early-stage cancer (p < 0.001), delays in adjuvant chemotherapy after curative surgery (p = 0.002), or delays in surveillance imaging for metastatic cancer (p < 0.001). The majority of providers early in the pandemic responded that “reducing risk of a complication from a COVID-19 infection to patients with cancer” was the primary reason for recommending delays in care (n = 52/76, 68%). Late in the pandemic, however, providers were more likely to agree that “any practice change would have a negative impact on patient outcomes” (p = 0.003). At both time points, the majority of providers agreed with the need for other care delivery changes, including screening patients for infectious symptoms (n = 128/132, 98%) and the use of telemedicine (n = 114/132, 86%) during the pandemic. Conclusions: We found significant differences in provider perspectives of delays in cancer care early versus late in the pandemic which reflects the swiftly evolving oncology practice during the COVID-19 pandemic. Future studies are needed to determine the impact of changes in treatment and care delivery on outcomes for patients with cancer.

The impact of COVID-19 on patients with cancer: A qualitative study

Background: The SARS-CoV-2/COVID-19 pandemic greatly impacted the health of many patients with cancer. We conducted in-depth interviews with patients across the United States to better understand the effect of the COVID-19 pandemic on their cancer care, emotional and mental health, and to solicit suggestions for how health care providers could mitigate these concerns. Methods: We contacted respondents from the Impact of COVID-19 on Cancer parent study. The parent study used a snowball sampling approach to survey patients nationally regarding cancer delays between April 2020 and October 2020. We invited all respondents who volunteered for future studies to participate in a 40-minute interview regarding their experiences and suggestions for how health care providers could mitigate COVID19-related concerns. Interviews were conducted between August 2020 and October 2020, recorded, transcribed and analyzed using qualitative thematic content analysis. Results: A total of 34 participants were contacted and consented to participate in this study. Four overarching themes were identified: (1) significant concern regarding infection risk;(2) concerns regarding care changes, such as delays, worsening cancer outcomes;(3) concern regarding loss of employment, health insurance, and transportation on cancer treatment, affordability, and prognosis;and (4) worsening emotional and mental health due to social isolation. Suggestions for the clinical team included: 1) specific and direct guidance from health care providers on how to mitigate infection risk;2) screening for and access to mental health services;3) continuation of cancer treatment, surveillance, and clinical trials without delays and 4) allowing caregivers to attend appointments. Conclusions: In this national qualitative study of patients with cancer, participants identified that COVID-19 and modifications to their cancer care worsened their emotional and mental health with growing concerns about the impact of the virus and socioeconomic status on their cancer outcomes. Specific suggestions for health care providers, such as anticipatory guidance, access to mental health services, and expanded visitation should be considered to improve patient experiences with care during the pandemic.