International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 06 | June 2022
p-ISSN: 2395-0072
www.irjet.net
Covid-19 Detection Using Deep Neural Networks. Prakash Upadhyay, Dhairya Shah, Jigar Vaishnav, Miloni Shah Thakur College of Engineering and Technology (TCET) Kandivali (East), Mumbai - 101 ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Covid-19 is inciting panic amongst people for
will allow us to predict the chances of a person being COVID 19 positive at an early stage and it will also create awareness among other individuals. A huge amount of data can be pooled from millions of people, and this will enable us to improve the accuracy of the model.
several reasons. It’s a new virus and currently there is no vaccine or cure. Its novelty means that doctors and scientist are not sure how it behaves and how it might evolve. The World Health Organization (WHO) labeled the virus as a pandemic. In this wave of panic a neural network that could help in early detection of COVID 19 in patients would help put people’s minds at ease. The proposed Neural Network will input the symptoms that people are experiencing along with other data relevant to prediction of COVID 19 like age, recent travel history, etc. These features will be entered into the Neural Network, and it will predict the probable chance that you might have contracted COVID 19. This Neural Network will not only impact people’s lives but also create a sense of awareness among people.
2. DESIGN
Key Words: Artificial Intelligence, Reinforcement Learning, Deep Neural Networks, Covid-19, CNN.
1. INTRODUCTION The coronavirus outbreak has not only infected millions of people but has also led to thousands of deaths. This virus, despite having lower fatality rate, has caused thrice the number of deaths as compared to the combined number of deaths caused by both MERS and SARS. This is majorly caused by the fact that COVID 19 is highly contagious. It has been observed that the symptoms of COVID-19 are like that of common influenza, which makes it difficult to detect. Due to these factors, it is critical to detect positive cases of COVID19 as early as possible so that we can prevent the spread of this pandemic. It is extremely necessary to make diagnostic tools that can aid in the detection of COVID-19. Deep neural network is a technology where there are multiple layers along with an input and output layer. Deep Neural Network aims at learning feature hierarchies. We are using symptoms of COVID 19 patients as the input features of deep neural networks. The symptoms will include running nose, fever, cold, cough, sore throat and it will also consider the age, history of pre-existing diseases and recent travel history of the person. We will collect data from patients admitted within various hospitals, this data will include records of patients who tested positive as well as those who tested negative for COVID-19. Our neural network model will analyze the symptoms of thousands of patients and also take into account external factors like their recent travel history, pre-existing diseases and all of this data will help it to generate precise prediction. This deep neural network model
© 2022, IRJET
|
Impact Factor value: 7.529
Fig.: Sequence Diagram for Application Architecture
3, The Application Architecture Application Architecture focuses on helping the user understand how the application works in the real world. To use the application, user access the web-based application using internet browser, after the access is granted, the user is presented with a friendly user interface in which user has to provide the information asked in the application which is then sent to the trained neural network. It includes information such as the symptoms of Covid – 19, age, and previous medical history and diseases etc. This information would help the trained neural network to find the probability that the user is suffering from Covid-19 and suggest helpful tips to ensure safety and good health. Thiis supposed to be the functioning of the application when the user will enter the details on the web application. The application can be used as many times as the user feel that
|
ISO 9001:2008 Certified Journal
|
Page 355