A multi model ensemble based deep convolution neural network structure for detection of COVID19.

The year 2020 will certainly be remembered for the COVID-19 outbreak. First reported in Wuhan city of China back in December 2019, the number of people getting affected by this contagious virus has grown exponentially. Given the population density of India, the implementation of the mantra of the test, track, and isolate is not obtaining satisfactory results. A shortage of testing kits and an increasing number of fresh cases encouraged us to come up with a model that can aid radiologists in detecting COVID19 using chest Xray images. In the proposed framework the low level features from the Chest X-ray images are extracted using an ensemble of four pre-trained Deep Convolutional Neural Network (DCNN) architectures, namely VGGNet, GoogleNet, DenseNet, and NASNet and later on are fed to a fully connected layer for classification. The proposed multi model ensemble architecture is validated on two publicly available datasets and one private dataset. We have shown that our multi model ensemble architecture performs better than single classifier. On the publicly available dataset we have obtained an accuracy of 88.98% for three class classification and for binary class classification we report an accuracy of 98.58%. Validating the performance on private dataset we obtained an accuracy of 93.48%. The source code and the dataset are made available in the github linkhttps://github.com/sagardeepdeb/ensemble-model-for-COVID-detection.

Harvesting of Autogenous Bone Graft from the Ascending Mandibular Ramus Compared with the Chin Region: a Systematic Review and Meta-Analysis Focusing on Complications and Donor Site Morbidity.

OBJECTIVES: The aim of this systematic review was to test the hypothesis of no difference in complications and donor site morbidity following harvesting of autogenous bone graft from the ascending mandibular ramus compared with the chin region. MATERIAL AND METHODS: MEDLINE (PubMed), Embase and Cochrane Library search in combination with a hand-search of relevant journals was conducted including human studies published in English through June 26, 2020. Randomized and controlled trials were included. Outcome measures included pain, infection, mucosal dehiscence, altered sensation or vitality of adjacent tooth/teeth, neurosensory disturbances and patient-reported outcome measures. Risk of bias was assessed by Cochrane risk of bias tool and Newcastle-Ottawa Scale. RESULTS: Ten controlled trials of high-quality fulfilled inclusion criteria. Risk of infection and mucosal dehiscence seems to be comparable with the two treatment modalities. However, harvesting from the chin seems to be associated with increased risk of pain, altered sensation or loss of tooth vitality, and neurosensory disturbances. Willingness to undergo the same treatment again was reported with both treatment modalities, but significant higher satisfaction, lower discomfort and acceptance of the surgical procedure was reported following harvesting from the ascending mandibular ramus. CONCLUSIONS: The hypothesis was rejected due to higher prevalence and severity of complications and donor site morbidity following harvesting of autogenous bone graft from the chin region. Dissimilar evaluation methods and various methodological confounding factors posed serious restrictions for literature review in a quantitative systematic manner. Conclusions drawn from results of this systematic review should therefore be interpreted with caution.