Machine learning from medical images: from photons to phenotype
A. Lisowska, A. O'Neil and I.Poole "Cross-cohort Evaluation of Machine Learning Approaches to Fall Detection from Accelerometer Data." In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, January 2018, ISBN 978-989-758-281-3, pages 77-82. DOI: 10.5220/0006554400770082
A. Lisowska, A. O’Neil, V.Dilys, M. Daykin, E.Beveridge, K. Muir, S. Mclaughlin, and I. Poole, "Context-Aware Convolutional Neural Networks for Stroke Sign Detection in Non-contrast CT Scans". In Annual Conference on Medical Image Understanding and Analysis, July 2017, pp. 494-505. Springer, Cham.
A. Lisowska, E.Beveridge, K. Muir and I.Poole "Thrombus Detection in CT Brain Scans using a Convolutional Neural Network". In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - Volume 2: BIOIMAGING, pp. 24-33 ISBN: 978-989-758-215-8
A. Lisowska, G. Wheeler, V. Inza, and I. Poole. "An Evaluation of Supervised, Novelty-Based and Hybrid Approaches to Fall Detection Using Silmee Accelerometer Data." In Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 10-16. 2015.
A. Lisowska, R. Annunziata, G. K. Loh, D. Karl, and E. Trucco, “An experimental assessment of five indices of retinal vessel tortuosity with the ret-tort public dataset,” in Proc. 36th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., Aug. 2014, pp. 5414–5417.