All Outputs (5)

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.

Modelling Variations in Newborn Life Support Procedure Using Colored Petri Nets (2022)
Conference Proceeding
Leva, M. C., Patelli, E., Podofillini, L., Wilson, S., Tan, A., Remenyte-Prescott, R., …Sharkey, D. (2022). Modelling Variations in Newborn Life Support Procedure Using Colored Petri Nets. In M. Chiara Leva, E. Patelli, L. Podofillini, & S. Wilson (Eds.), Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022) (489-496). https://doi.org/10.3850/978-981-18-5183-4_R12-08-152-cd

This research is conducted to study variations in the Newborn Life Support procedure. This procedure follows an evidence-based protocol to resuscitate and stabilize newborn babies requiring assistance at birth. Errors and ineffective actions in this... Read More about Modelling Variations in Newborn Life Support Procedure Using Colored Petri Nets.

Finding Comfortable Routes for Ambulance Transfers of Newborn Infants (2020)
Conference Proceeding
Partridge, T. J., Morris, D. E., Light, R. A., Leslie, A., Sharkey, D., Crowe, J. A., & McNally, D. S. (2020). Finding Comfortable Routes for Ambulance Transfers of Newborn Infants. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). https://doi.org/10.1109/EMBC44109.2020.9175873

Early inter-hospital ambulance transport of premature babies is associated with more severe brain injury. The mechanism is unclear, but they are exposed to excessive noise and vibration. Smart-routing may help minimise these exposure levels and poten... Read More about Finding Comfortable Routes for Ambulance Transfers of Newborn Infants.

Clinical Scene Segmentation with Tiny Datasets (2019)
Conference Proceeding
Smith, T. J., Sharkey, D., Crowe, J., & Valstar, M. (2019). Clinical Scene Segmentation with Tiny Datasets. In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) (1637-1645). https://doi.org/10.1109/ICCVW.2019.00203

Many clinical procedures could benefit from automatic scene segmentation and subsequent action recognition. Using Convolutional Neural Networks to semantically segment meaningful parts of an image or video is still an unsolved problem. This becomes e... Read More about Clinical Scene Segmentation with Tiny Datasets.

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.