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Dr Michael Mayo

Senior Lecturer (Computer Science)

Qualifications: BA(Hons) Otago PhD Cant

Contact Details

Email: michael.mayo@waikato.ac.nz
Room: G.2.24
Phone: +64 7 838 4403
Extension: 4403
Fax: +64 7 858 5095

Research Interests

Artificial intelligence (machine learning, evolutionary algorithms etc) and health/medicine. Some recent conference presentations: CGMs/privacy, improved Glucose Variability Percent metric.

Teaching Commitments

Recent Publications

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

  • 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

  • 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

  • Mayo, M., & Frank, E. (2018). Improving Naive Bayes for Regression with Optimised Artificial Surrogate Data. arXiv. Retrieved from http://arxiv.org/pdf/1707.04943v3

Find more research publications by Michael Mayo