no code implementations • 3 Feb 2020 • Steven Thompson, Paul Fergus, Carl Chalmers, Denis Reilly
Evaluation of the model is performed using a set of standard metrics which show the proposed model achieves high classification results in both training and validation using our windowing strategy, particularly W=500 (Sensitivity 0. 9705, Specificity 0. 9725, F1 Score 0. 9717, Kappa Score 0. 9430, Log Loss 0. 0836, ROCAUC 0. 9945).
no code implementations • 27 Aug 2019 • Casimiro Aday Curbelo Montañez, Paul Fergus, Carl Chalmers, Nurul Ahamed Hassain Malim, Basma Abdulaimma, Denis Reilly, Francesco Falciani
One of the most important challenges in the analysis of high-throughput genetic data is the development of efficient computational methods to identify statistically significant Single Nucleotide Polymorphisms (SNPs).
no code implementations • 6 Aug 2019 • Paul Fergus, Carl Chalmers, Casimiro Curbelo Montanez, Denis Reilly, Paulo Lisboa, Beth Pineles
Machine learning models, trained with FIGO and other user derived features extracted from CTG traces, have been shown to increase positive predictive capacity and minimise variability.