All Outputs (2)

Identifying Variation in the Newborn Life Support Procedure: An Automated Method (2023)
Conference Proceeding
Tan, A., Remenyte-Prescott, R., Egede, J., Valstar, M., & Sharkey, D. (2023). Identifying Variation in the Newborn Life Support Procedure: An Automated Method. In M. P. Brito, T. Aven, P. Baraldi, M. Čepin, & E. Zio (Eds.), Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023) (607-614)

This research is conducted for developing an automated method to recognize variations in the Newborn Life Support (NLS) procedure. Compliance with the NLS standard guideline is essential to prevent any adverse consequences for the newborn. Video reco... Read More about Identifying Variation in the Newborn Life Support Procedure: An Automated Method.

Small Sample Deep Learning for Newborn Gestational Age Estimation (2017)
Conference Proceeding
Torres Torres, M., Valstar, M. F., Henry, C., Ward, C., & Sharkey, D. (2017). Small Sample Deep Learning for Newborn Gestational Age Estimation. In Proceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017) (79-86). https://doi.org/10.1109/FG.2017.19

A baby’s gestational age determines whether or not they are preterm, which helps clinicians decide on suitable post-natal treatment. The most accurate dating methods use Ultrasound Scan (USS) machines, but these machines are expensive, require traine... Read More about Small Sample Deep Learning for Newborn Gestational Age Estimation.