Research Publications for Michael J Mayo

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Author's Publications

Publications ByMAYO, Michael J

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  • Hebert-Losier, K., Hanzlíková, I., Zheng, C., Streeter, L., & Mayo, M. (2019). The Deep Landing Error Scoring System calculation method can make an important difference!. In XXVII Congress of the International Society of Biomechanics. Calgary, Canada.

  • Mayo, M. (2019). Improving the robustness of the glycemic variability percentage metric to sensor dropouts in continuous glucose monitor data. In N. T. Nguyen, F. L. Gaol, T. P. Hong, & B. Trawinski (Eds.), Intelligent Information and Database Systems. ACIIDS 2019. Lecture Notes in Computer Science Vol. 11432 (pp. 373-384). Cham: Springer. doi:10.1007/978-3-030-14802-7_32

  • Podolskiy, V., Mayo, M., Koay, A., Gerndt, M., & Patros, P. (2019). Maintaining SLOs of cloud-native applications via self-adaptive resource sharing. In Proc 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2019) (pp. 72-81). Umeå, Sweden: IEEE. doi:10.1109/SASO.2019.00018

  • Mayo, M., & Daoud, M. (2019). Data normalisation using differential evolution and aggregated logistic functions. In Proc 2019 IEEE Congress on Evolutionary Computation (IEEE CEC 2019) (pp. 920-927). Wellington, NZ. doi:10.1109/CEC.2019.8790251

  • Mayo, M., & Yogarajan, V. (2019). A nearest neighbour-based analysis to identify patients from continuous glucose monitor data. In N. T. Nguyen, F. L. Gaol, T. P. Hong, & B. Trawinski (Eds.), Intelligent Information and Database Systems. ACIIDS 2019. Lecture Notes in Computer Science Vol. 11432 (pp. 349-360). Cham: Springer. doi:10.1007/978-3-030-14802-7_30

  • Daoud, M., Mayo, M., & Cunningham, S. J. (2019). RBFA: Radial Basis Function Autoencoders. In 2019 IEEE Congress on Evolutionary Computation (IEEE CEC 2019) (pp. 2966-2973). Wellington, NZ. doi:10.1109/CEC.2019.8790041

  • Mayo, M., Chepulis, L., & Paul, R. G. (2019). Glycemic-aware metrics and oversampling techniques for predicting blood glucose levels using machine learning. PLOS ONE, 14(12), e0225613. doi:10.1371/journal.pone.0225613

  • Daoud, M., & Mayo, M. (2019). A survey of neural network-based cancer prediction models from microarray data. Artificial Intelligence in Medicine, 97, 204-214. doi:10.1016/j.artmed.2019.01.006

  • Burnside, M., Crocket, H., Mayo, M., Pickering, J., Tappe, A., & de Bock, M. (2019). Do it yourself automated insulin delivery: A leading example of the democratization of medicine. Journal of Diabetes Science and Technology. doi:10.1177/1932296819890623

  • Daoud, M., & Mayo, M. (2018). A novel synthetic over-sampling technique for imbalanced classification of gene expressions using autoencoders and swarm optimization. In T. Mitrovic, B. Xue, & X. Li (Eds.), Proc 31st Australasian Joint Conference on Advances in Artificial Intelligence (AI 2018) Vol. LNAI 11320 (pp. 603-615). Conference held Wellington, NZ: Springer. doi:10.1007/978-3-030-03991-2_55

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