Ensemble Deep Learning Derived from Transfer Learning for Classification of COVID-19 Patients on Hybrid Deep-Learning-Based Lung Segmentation: A Data Augmentation and Balancing Framework.

BACKGROUND AND MOTIVATION: Lung computed tomography (CT) techniques are high-resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease control classification. Most artificial intelligence (AI) systems do not undergo generalization and are typically overfitted. Such trained AI systems are not practical for clinical settings and therefore do not give accurate results when executed on unseen data sets. We hypothesize that ensemble deep learning (EDL) is superior to deep transfer learning (TL) in both non-augmented and augmented frameworks. METHODOLOGY: The system consists of a cascade of quality control, ResNet-UNet-based hybrid deep learning for lung segmentation, and seven models using TL-based classification followed by five types of EDL's. To prove our hypothesis, five different kinds of data combinations (DC) were designed using a combination of two multicenter cohorts-Croatia (80 COVID) and Italy (72 COVID and 30 controls)-leading to 12,000 CT slices. As part of generalization, the system was tested on unseen data and statistically tested for reliability/stability. RESULTS: Using the K5 (80:20) cross-validation protocol on the balanced and augmented dataset, the five DC datasets improved TL mean accuracy by 3.32%, 6.56%, 12.96%, 47.1%, and 2.78%, respectively. The five EDL systems showed improvements in accuracy of 2.12%, 5.78%, 6.72%, 32.05%, and 2.40%, thus validating our hypothesis. All statistical tests proved positive for reliability and stability. CONCLUSION: EDL showed superior performance to TL systems for both (a) unbalanced and unaugmented and (b) balanced and augmented datasets for both (i) seen and (ii) unseen paradigms, validating both our hypotheses.

Recent Developments in Nanotechnology-Based Biosensors for the Diagnosis of Coronavirus

The major challenge in today's world is that medical research is facing the existence of a vast number of viruses and their mutations, which from time to time cause outbreaks. Also, the continuous and spontaneous mutations occurring in the viruses and the emergence of resistant virus strains have become serious medical hazards. So, in view of the growing number of diseases, like the recent COVID-19 pandemic that has caused the deaths of millions of people, there is a need to improve rapid and sensitive diagnostic strategies to initiate timely treatment for such conditions. In the cases like COVID-19, where a real cure due to erratic and ambiguous signs is not available, early intervention can be life-saving. In the biomedical and pharmaceutical industries, nanotechnology has evolved exponentially and can overcome multiple obstacles in the treatment and diagnosis of diseases. Nanotechnology has developed exponentially in the biomedical and pharmaceutical fields and can overcome numerous challenges in the treatment and diagnosis of diseases. At the nano stage, the molecular properties of materials such as gold, silver, carbon, silica, and polymers get altered and can be used for the creation of reliable and accurate diagnostic techniques. This review provides insight into numerous diagnostic approaches focused on nanoparticles that could have been established for quick and early detection of such diseases.

Recent Developments in Nanotechnology-Based Biosensors for the Diagnosis of Coronavirus.

The major challenge in today's world is that medical research is facing the existence of a vast number of viruses and their mutations, which from time to time cause outbreaks. Also, the continuous and spontaneous mutations occurring in the viruses and the emergence of resistant virus strains have become serious medical hazards. So, in view of the growing number of diseases, like the recent COVID-19 pandemic that has caused the deaths of millions of people, there is a need to improve rapid and sensitive diagnostic strategies to initiate timely treatment for such conditions. In the cases like COVID-19, where a real cure due to erratic and ambiguous signs is not available, early intervention can be life-saving. In the biomedical and pharmaceutical industries, nanotechnology has evolved exponentially and can overcome multiple obstacles in the treatment and diagnosis of diseases. Nanotechnology has developed exponentially in the biomedical and pharmaceutical fields and can overcome numerous challenges in the treatment and diagnosis of diseases. At the nano stage, the molecular properties of materials such as gold, silver, carbon, silica, and polymers get altered and can be used for the creation of reliable and accurate diagnostic techniques. This review provides insight into numerous diagnostic approaches focused on nanoparticles that could have been established for quick and early detection of such diseases.

An Epidemiological Analysis of SARS-CoV-2 Genomic Sequences from Different Regions of India.

The number of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) cases is increasing in India. This study looks upon the geographic distribution of the virus clades and variants circulating in different parts of India between January and August 2020. The NPS/OPS from representative positive cases from different states and union territories in India were collected every month through the VRDLs in the country and analyzed using next-generation sequencing. Epidemiological analysis of the 689 SARS-CoV-2 clinical samples revealed GH and GR to be the predominant clades circulating in different states in India. The northern part of India largely reported the 'GH' clade, whereas the southern part reported the 'GR', with a few exceptions. These sequences also revealed the presence of single independent mutations-E484Q and N440K-from Maharashtra (first observed in March 2020) and Southern Indian States (first observed in May 2020), respectively. Furthermore, this study indicates that the SARS-CoV-2 variant (VOC, VUI, variant of high consequence and double mutant) was not observed during the early phase of virus transmission (January-August). This increased number of variations observed within a short timeframe across the globe suggests virus evolution, which can be a step towards enhanced host adaptation.

COVID-19: Asymptomatic Carrier: An Autopsy Case Report.

The severe acute respiratory syndrome (SARS)-coronavirus- 2 (CoV-2) outbreak in Wuhan, China has now spread to many countries across the world including the India with an increasing death toll. On March 11, 2020, the new clinical condition COVID-19 (Corona-Virus-Disease-19) was declared a pandemic by the World Health Organization (WHO). Owing to its infectivity, high risk of transmission, and limited handling of dead bodies, published data on the course of diseases has been limited. Most patients with COVID-19 have a mild disease course and remain as asymptomatic carrier; however, few patients of older age and with co-morbidites develop severe disease leading on to fatality. If due to COVID-19 infection death occurs, an autopsy is unlikely. However in unnatural deaths the legal duty impels the proper performance of a full autopsy, to find out the cause and manner of death. The detailed autopsy examination along with histo-pathological findings in the organs of asymptomatic patient of COVID-19 and its comparison with microscopic findings in Aluminium Phosphide poisoning are discussed below. This will summarizes the research status for COVID-19 deaths, which will be important for evaluation of cause of death, prevention, control and clinical strategies of COVID-19.