Abstract
COVID-19 (Coronavirus 2019) has now shown a
flattening curve as the impact of increased immunity system
through vaccination or natural infection. However, experience
and data suggest new variants can emerge at any time.
Therefore, research in this topic is still rising. The Artificial
Intelligence (AI) can help the health practitioners and medical
personnel to understand the problems caused by this disease
based on the historical data. Usually, the progress of the patients
in a hospital are monitored by the nurse or the doctors in daily
basis. Especially when they are in the critical stage of the illness.
They take the reading from the devices to monitor the vital signs.
In this study, we aim to explain the vital sign causal relationship
by using one of the Bayesian Network (BN) method, namely PC
algorithm. The result shows that causal relationship from died
patients vital signs is different and unexplainable due to many
failures of the body to regulate the flow of oxygen supply.
flattening curve as the impact of increased immunity system
through vaccination or natural infection. However, experience
and data suggest new variants can emerge at any time.
Therefore, research in this topic is still rising. The Artificial
Intelligence (AI) can help the health practitioners and medical
personnel to understand the problems caused by this disease
based on the historical data. Usually, the progress of the patients
in a hospital are monitored by the nurse or the doctors in daily
basis. Especially when they are in the critical stage of the illness.
They take the reading from the devices to monitor the vital signs.
In this study, we aim to explain the vital sign causal relationship
by using one of the Bayesian Network (BN) method, namely PC
algorithm. The result shows that causal relationship from died
patients vital signs is different and unexplainable due to many
failures of the body to regulate the flow of oxygen supply.
| Original language | English |
|---|---|
| Title of host publication | Second International Conference on Software Engineering and Information Technology (ICoSEIT) |
| Publisher | IEEE |
| Pages | 37-41 |
| Number of pages | 5 |
| ISBN (Electronic) | 979-8-3503-1750-3 |
| ISBN (Print) | 979-8-3503-1751-0 |
| DOIs | |
| Publication status | Published - 16 Apr 2024 |
| Event | 2024 2nd International Conference on Software Engineering and Information Technology - Bandung, Indonesia Duration: 28 Feb 2024 → 29 Feb 2024 Conference number: 2nd |
Conference
| Conference | 2024 2nd International Conference on Software Engineering and Information Technology |
|---|---|
| Abbreviated title | ICoSEIT |
| Country/Territory | Indonesia |
| City | Bandung |
| Period | 28/02/24 → 29/02/24 |