Eugene M Dempsey
Biographic Data
| ID | 10456915 |
|---|---|
| NAME | Eugene M Dempsey |
| GIVEN NAMES | Eugene M |
| FAMILY NAME | Dempsey |
| SIGNATURE | DEMPSEY E M |
| AFFILIATIONS | Department of Neonatology, Cork University Maternity Hospital, Wilton, T12 K8AF Cork, Ireland |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Machine Learning Detects Intraventricular Haemorrhage in Extremely Preterm Infants
There was a significant association between the data-driven definition of PRDs in rcSO 2 and brain injury. Automated analysis of PRDs of the cerebral NIRS signal in extremely preterm infants may aid in better prediction of IVH compared with a threshold-based approach. Further investigation of the definition of the extracted PRDs and an understanding of the physiology underlying these events are required
In-Silico Evaluation of Anthropomorphic Measurement Variations on Electrical Cardiometry in Neonates
Non-invasive cardiac output methods such as Electrical Cardiometry (EC) are relatively novel assessment tools for neonates and they enable continuous monitoring of stroke volume (SV). An in-silico comparison of differences in EC-derived SV in relation to preset length and weight was performed. EC (ICON, Osypka Medical) was simulated using the "demo" mode for various combinations of length and weight representative of term and preterm infants. One…
No prominent works on this page.
In-Silico Evaluation of Anthropomorphic Measurement Variations on Electrical Cardiometry in Neonates
Non-invasive cardiac output methods such as Electrical Cardiometry (EC) are relatively novel assessment tools for neonates and they enable continuous monitoring of stroke volume (SV). An in-silico comparison of differences in EC-derived SV in relation to preset length and weight was performed. EC (ICON, Osypka Medical) was simulated using the "demo" mode for various combinations of length and weight representative of term and preterm infants. One…
Machine Learning Detects Intraventricular Haemorrhage in Extremely Preterm Infants
There was a significant association between the data-driven definition of PRDs in rcSO 2 and brain injury. Automated analysis of PRDs of the cerebral NIRS signal in extremely preterm infants may aid in better prediction of IVH compared with a threshold-based approach. Further investigation of the definition of the extracted PRDs and an understanding of the physiology underlying these events are required
Internal Medicine (2 works) · Medicine (2 works) · Neonatal Respiratory Health Research (2 works) · Anesthesia (1 work) · Biomedical Engineering (1 work) · Blood pressure (1 work) · Body weight (1 work) · Congenital Heart Disease Studies (1 work) · Gestational age (1 work) · Heart rate (1 work)