Cardiac patients’ surgery outcome and associated factors in Ethiopia: application of Machine learning
Cardiac patients’ surgery outcome and associated factors in Ethiopia: application of Machine learning
| Accessed Date | 2024-04-18T11:11:29Z | |
| Date Availabe | 2024-04-18T11:11:29Z | |
| Issued Date | 2024 | |
| Description | In this retrospective cohort, a total of 1,520 cardiac patients who were on follow up from February 2012- January 2023 in two cardiac centers (ElOuzeir Cardiac Center and cardiac center Ethiopia) were included. Saturated oxygen, age, ejection fraction, duration of cardiac center stays after surgery, waiting time to surgery, haemoglobin value, and creatinine value were assessed. Machine learning algorism Their charts were reviewed and machine learning algorithms were applied for data analysis. For machine learning algorithms comparison, lift and AUC was applied. | |
| URI | https://rdmc.aphi.gov.et/handle/123456789/87 | |
| Language | en | |
| Title | Cardiac patients’ surgery outcome and associated factors in Ethiopia: application of Machine learning | |
| Type | Dataset | |
| Entity Type | ||
| Geographic Coverage | National | |
| Sex Coverage | Yes | |
| Format | CSV | |
| RDMC ID | APHI-RDMC-042 | |
| Keyword | Machine learning, Cardiac disease, Ethiopia, Cardiac surgery | |
| Objective | The main objective of the current study was to assess the prevalence of death due to cardiac disease and its risk factors of among heart patients in Ethiopia. |
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