Mobile App for the information management of pre-existing diseases towards preventing COVID-19 severity
13th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2023
; : 541-546, 2023.
Article
in English
| Scopus | ID: covidwho-2320128
ABSTRACT
World Health Organization (WHO) studies indicate that people with pre-existing diseases are prone to suffer the severity of the effects of COVID-19 in case of infection. This work presents a mobile application development through open-source software and machine learning techniques for the prediction of the COVID-19 severity in an individual based on pre-existing disease information. For the prediction of the severity and to determine the possibility that an individual ends up in an intensive care unit (ICU), we set a machine learning algorithm, which resulted in a higher probability of prediction when the user undergoes cases of pre-existing diseases, with an efficiency rate of 98 %. We carried out load and stress testing to verify the processing performance, battery consumption, startup latency, and maximum amount of user connections supported by the application, complemented with a wristband for individual's real-time monitoring to attain low battery consumption when using public cloud services and low-power technologies for the connection. © 2023 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
13th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2023
Year:
2023
Document Type:
Article
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