Outputs (3)

Artificial intelligence surgery: how do we get to autonomous actions in surgery? (2021)
Journal Article
GUMBS, A.A., FRIGERIO, I., SPOLVERATO, G., CRONER, R., ILLANES, A., CHOUILLARD, E. and ELYAN, E. 2021. Artificial intelligence surgery: how do we get to autonomous actions in surgery? Sensors [online], 21(16), article 5526. Available from: https://doi.org/10.3390/s21165526

Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intel... Read More about Artificial intelligence surgery: how do we get to autonomous actions in surgery?.

Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. (2021)
Presentation / Conference Contribution
DANG, T., NGUYEN, T.T., MORENO-GARCIA, C.F., ELYAN, E. and MCCALL, J. 2021. Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. In Proceeding of 2021 IEEE (Institute of electrical and electronics engineers) Congress on evolutionary computation (CEC 2021), 28 June - 1 July 2021, Kraków, Poland : [virtual conference]. Piscataway: IEEE [online], pages 744-751. Available from: https://doi.org/10.1109/CEC45853.2021.9504929

In recent years, deep learning has rapidly become a method of choice for segmentation of medical images. Deep neural architectures such as UNet and FPN have achieved high performances on many medical datasets. However, medical image analysis algorith... Read More about Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation..

The utility of mathematical fitness-fatigue models for assisting with the planning of physical training for sport: from in silico experiments employing synthetic data, lower-bound operational conditions and model estimation, to the development of software resources for future research. (2021)
Thesis
STEPHENS HEMINGWAY, B.H. 2021. The utility of mathematical fitness-fatigue models for assisting with the planning of physical training for sport: from in silico experiments employing synthetic data, lower-bound operational conditions and model estimation, to the development of software resources for future research. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1603154

The greatest potential application of mathematical models in sport science is to predict future performance of individual athletes in response to training, with sufficient accuracy to assist with planning of training programs and short tapering perio... Read More about The utility of mathematical fitness-fatigue models for assisting with the planning of physical training for sport: from in silico experiments employing synthetic data, lower-bound operational conditions and model estimation, to the development of software resources for future research..