ABSTRACT
Pandemic and natural disasters are growing more often, imposing even more pressure on life care services and users. There are knowledge gaps regarding how to prevent disasters and pandemics. In recent years, after heart disease, corona virus disease-19 (COVID-19), brain stroke, and cancer are at their peak. Different machine learning and deep learning-based techniques are presented to detect these diseases. Existing technique uses two branches that have been used for detection and prediction of disease accurately such as brain hemorrhage. However, existing techniques have been focused on the detection of specific diseases with double-branches convolutional neural networks (CNNs). There is a need to develop a model to detect multiple diseases at the same time using computerized tomography (CT) scan images. We proposed a model that consists of 12 branches of CNN to detect the different types of diseases with their subtypes using CT scan images and classify them more accurately. We proposed multi-branch sustainable CNN model with deep learning architecture trained on the brain CT hemorrhage, COVID-19 lung CT scans and chest CT scans with subtypes of lung cancers. Feature extracted automatically from preprocessed input data and passed to classifiers for classification in the form of concatenated feature vectors. Six classifiers support vector machine (SVM), decision tree (DT), K-nearest neighbor (K-NN), artificial neural network (ANN), naïve Bayes (NB), linear regression (LR) classifiers, and three ensembles the random forest (RF), AdaBoost, gradient boosting ensembles were tested on our model for classification and prediction. Our model achieved the best results on RF on each dataset. Respectively, on brain CT hemorrhage achieved (99.79%) accuracy, on COVID-19 lung CT scans achieved (97.61%), and on chest CT scans dataset achieved (98.77%). © 2023 Wiley Periodicals LLC.
ABSTRACT
Background: Growing evidence shows that a significant number of patients with COVID-19 experience prolonged symptoms, known as Long COVID. COVID-19, caused by SARS-CoV-2, can involve sequelae that last weeks to months after initial recovery. The objective of this study is to assessing the long-term effects of COVID-19 and estimate the prevalence of each symptom of patients at a post-COVID-19 stage. Aim(s): This study was conducted to determine the frequency of post COVID effects among symptomatic and asymptomatic patients at a tertiary hospital Lahore, Pakistan. Material(s) and Method(s): This cross-sectional study was conducted among the population (such as doctors, nurses, paramedical staff, students and faculty) at a tertiary hospital Lahore, Pakistan. This study included 30 participants and the collected data had been checked, coded, entered and exported at SPSS version 25 for analysis. Pearson chi square test was used for the statistical analysis of the data. Result(s): Among 30 participants, no one show symptoms of hypertension, diabetes mellitus and visual problems during COVID-19 and after recovery.8 patients were asymptomatic and 22patients were symptomatic which shows post COVID effects such as which include dyspnea (67.7%), mental confusion (26.7%), tiredness (93%), chest pain (16.7%), anorexia(26%), insomnia(26%), dyspepsia(67%), headache(66.7%), fatigue(50%), fever(10%), loss of smell(33%), weakness(40%), hypoxia on altitude(60%), breathlessness(70%), arthrgia(13.3%), mental confusion(26.7%), post-exertinal malasia(16.7%), sore throat(10%), joint pain(40%) Conclusion(s): Conclusion based on the study result that most common post-COVID long terms effects are dyspnea, weight loss, mental confusion, anorexia, arthrgia, post-exertinal malsiae, insomnia, fever, hypoxia, breathlessness, sore throat. Symptoms can be controlled by taking proper precautionary measure and strict following on PPE. The problem can only get worse with time if not followed PPE Copyright © 2022 Lahore Medical And Dental College. All rights reserved.
ABSTRACT
Background: The education of college level badly affected by the Covid-19 because of several reasons. The educational activities of college level are neglected and the education system is becoming unsatisfactory during the deteriorated era of Covid-19. Objectives: The aim of study is to identify the impact of Covid-19 on the academic achievement of student of district Faisalabad. Methodology: Total population will be 267 students of graduation 4th year in the colleges of (Government College for women Karkhana bazar Faisalabad 101, Government Degree College Samanabad 77 and Government postgraduate Islamiya College for women Eidgah road Faisalabad 89). The sample size of this study was 134 (Government college for women karkhana bazar Faisalabad 54, Government degree college Samanabad 38 and Government postgraduate Islamiya college for women Eidgah road Faisalabad 42) by the confidence interval 6% and confidence level 95%.The sample size had been determined by using online available software i.e;www.surveysystem.com. Respondents were selected for research by simple random sampling technique. The data were collected through questionnaire keeping in view the objectives of the study. Collected data were analyzed by using Statistical Package for Social Sciences (SPSS). The respondents of the present study were asked to give their opinion on a five Likert scale. The percentage, mean, standard deviation and rank order were calculated for presents the results. Conclusion: The study was concluded that students were faced numerous social problems due to the spreading of Covid-19 in all over the world. These social problems directly affected the educational system of every country. On the basis of results, it was concluded that the Covid-19 completely deteriorated the educational system and academic achievements of students. So it becomes crucial to reconstruct every fiber of educational society so that development of student’s academic achievement can be enhanced.