| Autor: |
R.P. dos Santos, D. Silva, A. Menezes, S. Lukasewicz, C.H. Dalmora, O. Carvalho, J. Giacomazzi, N. Golin, R. Pozza, T.A. Vaz |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Infection Prevention in Practice, Vol 3, Iss 3, Pp 100167- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2590-0889 |
| DOI: |
10.1016/j.infpip.2021.100167 |
| Popis: |
Summary: Healthcare-associated infections (HAIs) are among the most common adverse events in hospitals. We used artificial intelligence (AI) algorithms for infection surveillance in a cohort study. The model correctly detected 67 out of 73 patients with HAIs. The final model used a multilayer perceptron neural network achieving an area under receiver operating curve (AUROC) of 90.27%; specificity of 78.86%; sensitivity of 88.57%. Respiratory infections had the best results (AUROC ≥93.47%). The AI algorithm could identify most HAIs. AI is a feasible method for HAI surveillance, has the potential to save time, promote accurate hospital-wide surveillance, and improve infection prevention performance. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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