Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add filters

Database
Language
Document Type
Year range
1.
2021 International Conference on Communication, Control and Information Sciences, ICCISc 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1379527

ABSTRACT

COVID-19 infection, caused by the virus SARS-Cov 2 is growing at a rapid rate. As an efficient cure has not been available, early detection is integral for disease cure and control. Predictive algorithms are useful in this scenario. Here, estimation is performed on patients who are likely to come in contact with COVID-19 disease, using clinical predictive models with the help of deep learning. The most informative features are extracted from chest X-ray images for COVID-19 patients and non COVID-19 patients. These images are used for COVID detection. Patients with other chronic diseases are more vulnerable to COVID-19. Hence, we put forward a Heart Disease Prediction system based on machine learning algorithms. The feature selection algorithms are utilized in the feature selection procedures for enhancing the classification accuracy and for minimizing the execution time of the classification system. © 2021 IEEE.

SELECTION OF CITATIONS
SEARCH DETAIL