A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening

Figueredo, Grazziela P.; Shi, Peng; Parkes, Andrew J.; Evans, Keith; Garibaldi, Jonathan M.; Negm, Ola; Tighe, Patrick J.; Sewell, Herbert F.; Robertson, John

doi:10.1109/CEC.2019.8790316

All Outputs (3)

A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices (2019)
Journal Article
Cui, T., Bai, R., Ding, S., Parkes, A. J., Qu, R., He, F., & Li, J. (2020). A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices. Soft Computing, 24, 2809–2831. https://doi.org/10.1007/s00500-019-04517-y

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Portfolio optimization is one of the most important problems in the finance field. The traditional Markowitz mean-variance model is often unrealistic since it relies on the perfect market... Read More about A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices.

Pattern-Based Approach to the Workflow Satisfiability Problem with User-Independent Constraints (2019)
Journal Article
Karapetyan, D., J. Parkes, A., Gutin, G., & Gagarin, A. (2019). Pattern-Based Approach to the Workflow Satisfiability Problem with User-Independent Constraints. Journal of Artificial Intelligence Research, 66, 85-122. https://doi.org/10.1613/jair.1.11339

The fixed parameter tractable (FPT) approach is a powerful tool in tackling computationally hard problems. In this paper, we link FPT results to classic artificial intelligence (AI) techniques to show how they complement each other. Specifically, we... Read More about Pattern-Based Approach to the Workflow Satisfiability Problem with User-Independent Constraints.

A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening (2019)
Presentation / Conference Contribution
Figueredo, G. P., Shi, P., Parkes, A. J., Evans, K., Garibaldi, J. M., Negm, O., …Robertson, J. (2019). A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening. In 2019 IEEE Congress on Evolutionary Computation (CEC) (95-102). https://doi.org/10.1109/CEC.2019.8790316

Current methods to identify cutoff values for tumour-associated molecules (antigens) discrimination are based on statistics and brute force. These methods applied to cancer screening problems are very inefficient, especially with large data sets with... Read More about A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening.