Thijmen Kupers
Biographic Data
| ID | 8269041 |
|---|---|
| NAME | Thijmen Kupers |
| GIVEN NAMES | Thijmen |
| FAMILY NAME | Kupers |
| SIGNATURE | KUPERS T |
| AFFILIATIONS | University Medical Center Groningen |
| ORCID | 0009-0000-4958-7488 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Using Vital Signs for the Early Prediction of Necrotizing Enterocolitis in Preterm Neonates with Machine Learning
Using vital signs, we predicted NEC in the first 5 postnatal days with an F1-score up to 0.82. Splanchnic and cerebral oxygenation were the most contributing vital predictors. This pioneering effort in early NEC prediction using vital signs underscores the potential for targeted preventive measures and also emphasizes the need for additional data in future studies
No prominent works on this page.
Using Vital Signs for the Early Prediction of Necrotizing Enterocolitis in Preterm Neonates with Machine Learning
Using vital signs, we predicted NEC in the first 5 postnatal days with an F1-score up to 0.82. Splanchnic and cerebral oxygenation were the most contributing vital predictors. This pioneering effort in early NEC prediction using vital signs underscores the potential for targeted preventive measures and also emphasizes the need for additional data in future studies
Anesthesia (1 work) · Computer Science (1 work) · Gestational age (1 work) · Infant Development and Preterm Care (1 work) · Infant Nutrition and Health (1 work) · Internal Medicine (1 work) · Logistic regression (1 work) · Machine learning (1 work) · Medicine (1 work) · Necrotizing Enterocolitis (1 work)