Prediction of Serious Adverse Events from Nighttime Vital Signs Values.
Annu Int Conf IEEE Eng Med Biol Soc
; 2022: 2631-2634, 2022 07.
Article
en En
| MEDLINE
| ID: mdl-36086507
ABSTRACT
The period directly following surgery is critical for patients as they are at risk of infections and other types of complications, often summarized as severe adverse events (SAE). We hypothesize that impending complications might alter the circadian rhythm and, therefore, be detectable during the night before. We propose a SMOTE-enhanced XGBoost prediction model that classifies nighttime vital signs depending on whether they precede a serious adverse event or come from a patient that does not have a complication at all, based on data from 450 postoperative patients. The approach showed respectable results, producing a ROC-AUC score of 0.65 and an accuracy of 0.75. These findings demonstrate the need for further investigation.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Signos Vitales
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Año:
2022
Tipo del documento:
Article