A Machine learning Classification approach for detection of Covid 19 using CT images

Coronavirus disease 2019 popularly known as COVID 19 was first found in Wuhan, China in December 2019. World Health Organization declared Covid 19 as a transmission disease. The symptoms were cough, loss of taste, fever, tiredness, respiratory problem. These symptoms were likely to show within 11 –14 days. The RT-PCR and rapid antigen biochemical tests were done for the detection of COVID 19. In addition to biochemical tests, X-Ray and Computed Tomography (CT) images are used for the minute details of the severity of the disease. To enhance efficiency and accuracy of analysis/detection of COVID images and to reduce of doctors' time for analysis could be addressed through Artificial Intelligence. The dataset from Kaggle was utilized to analyze. The statistical and GLCM features were extracted from CT images for the classification of COVID and NON-COVID instances in this study. CT images were used to extract statistical and GLCM features for categorization. In the proposed/prototype model, we achieved the classification accuracy of 91%, and 94.5% using SVM and Random Forest respectively

Development and evaluation of gastro retentive floating tablets of anti hyperlipidemic drug

The aim of the present study was to develop Gastro retentive effervescent floating tablets (GREFT) containing 20 mg of simvastatin were developed by direct compression method using HPMC K4M, HPMC K15M, HPMC K100M with different drug to polymer ratio. Tablets were evaluated for their physical characteristics, viz., hardness, friability, drug content and floating properties. Further, tablets were studied for in vitro drug release characteristics for 12 h. The tablets exhibited controlled and prolonged drug release, with optimum hardness, consistent uniformity in weight and low friability. The formulation with F2 (HPMC K100M 1:3 ratio) showed 85.83 % drug release at the end of 12 h and exhibited optimum floating lag time. A decrease in release rate of the drug was observed on increasing polymer ratio and also by increasing viscosity grades of the polymer (HPMC). Drug release from effervescent floating matrix tablets was sustained over 12 h with buoyant properties. DSC study revealed that there is no drug excipient interaction. Based on the release kinetics, all formulations best fitted the Higuchi, first-order model and non-Fickian as the mechanism of drug release. Optimized formulation (F9) was selected based on the similarity factor (f2) (71.32) and invitro dissolution was used in radiographic studies by incorporating BaSO4. In vivo X-ray studies in human volunteers showed that the mean gastric residence time was 5.4 ± 0.32 h