Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network
Since February 2020, the world has been engaged in an intense struggle with the COVID-19 disease, and health systems have come under tragic pressure as the disease turned into a pandemic. The aim of this study is to obtain the most effective routine blood values (RBV) in the diagnosis and prognosis...
Main Authors: | Mehmet Tahir Huyut, Andrei Velichko |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-06-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/13/4820 |
Similar Items
-
LogNNet model as a fast, simple and economical AI instrument in the diagnosis and prognosis of COVID-19
by: Mehmet Tahir Huyut, et al.
Published: (2023-01-01) -
A Method for Medical Data Analysis Using the LogNNet for Clinical Decision Support Systems and Edge Computing in Healthcare
by: Andrei Velichko
Published: (2021-09-01) -
Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application
by: Andrei Velichko, et al.
Published: (2022-10-01) -
A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks
by: Andrei Velichko, et al.
Published: (2021-10-01) -
Neural Network Entropy (NNetEn): Entropy-Based EEG Signal and Chaotic Time Series Classification, Python Package for NNetEn Calculation
by: Andrei Velichko, et al.
Published: (2023-05-01)