A lightweight CORONA-NET for COVID-19 detection in X-ray images

Since December 2019, COVID-19 has posed the most serious threat to living beings. With the advancement of vaccination programs around the globe, the need to quickly diagnose COVID-19 in general with little logistics is fore important. As a consequence, the fastest diagnostic option to stop COVID-19 from spreading, especially among senior patients, should be the development of an automated detection system. This study aims to provide a lightweight deep learning method that incorporates a convolutional neural network (CNN), discrete wavelet transform (DWT), and a long short-term memory (LSTM), called CORONA-NET for diagnosing COVID-19 from chest X-ray images. In this system, deep feature extraction is performed by CNN, the feature vector is reduced yet strengthened by DWT, and the extracted feature is detected by LSTM for prediction. The dataset included 3000 X-rays, 1000 of which were COVID-19 obtained locally. Within minutes of the test, the proposed test platform's prototype can accurately detect COVID-19 patients. The proposed method achieves state-of-the-art performance in comparison with the existing deep learning methods. We hope that the suggested method will hasten clinical diagnosis and may be used for patients in remote areas where clinical labs are not easily accessible due to a lack of resources, location, or other factors.

Clinical course and outcome of snake envenomation at a hospital in Karachi

INTRODUCTION

Snake envenomation is a frequently reported medical emergency at the Civil Hospital Karachi, Pakistan, [corrected] thus obviating the need to assess the patterns of the clinical course and outcome of snake envenomation cases.

METHODS

The demographic characteristics, clinical signs and symptoms, laboratory findings, treatment and outcome of 80 victims of snake bite were recorded. These patients were admitted to the Civil Hospital Karachi between January 2006 and September 2007. The data of all the cases was analysed statistically using the Statistical Package for the Social Sciences version 11.0.

RESULTS

The majority of the 80 victims of snake bite were male (80 percent) and 20 percent were female. The mean age of the patients was 33.3 years. The main type of envenomation was vasculotoxic (92.5 percent), and none were neurotoxic or myotoxic. Both local and systemic clinical features of envenomation were present. Bleeding was reported in 43.8 percent of the patients. 71.3 percent of the patients showed coagulopathy of defibrination and the anti-coagulant type. All patients received anti-snake venom. Five (6.3 percent) patients in the study died.

CONCLUSION

The most common type of snake envenomation in this part of the province of Sindh is vasculotoxic due to the high inhabitancy of Viperidae. High morbidity and mortality rates can be reduced significantly through patient education on the precautions that need to be taken by farmers and field workers against snake bite. Early referral to a well-equipped health facility is necessary, as the mortality rate was high among those patients who arrived late.