Now showing items 1-2 of 2

  • Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. 

    Regnier-Coudert, Olivier; McCall, John; Lothian, Robert; Lam, Thomas; McClinton, Sam; N'Dow, James (Elsevier https://doi.org/10.1016/j.artmed.2011.11.003, 2011-12-27)
    REGNIER-COUDERT, O., MCCALL, J., LOTHIAN, R., LAM, T., MCCLINTON, S. and N'DOW, J. 2012. Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. Artificial intelligence in medicine [online], 55(1), pages 25-35. Available from: https://doi.org/10.1016/j.artmed.2011.11.003
    Objectives: Prediction of prostate cancer pathological stage is an essential step in a patient's pathway. It determines the treatment that will be applied further. In current practice, urologists use the pathological stage ...
  • Truck and trailer scheduling in a real world, dynamic and heterogeneous context. 

    Regnier-Coudert, Olivier; McCall, John; Ayodele, Mayowa; Anderson, Steven (Elsevier http://dx.doi.org/10.1016/j.tre.2016.06.010, 2016-07-14)
    REGNIER-COUDERT, O., MCCALL, J., AYODELE, M. and ANDERSON, S. 2016. Truck and trailer scheduling in a real world, dynamic and heterogeneous context. Transportation research part E: logistics and transportation review [online], 93, pages 389-408. Available from: http://dx.doi.org/10.1016/j.tre.2016.06.010
    We present a new variant of the Vehicle Routing Problem based on a real industrial scenario. This VRP is dynamic and heavily constrained and uses time-windows, a heterogeneous vehicle fleet and multiple types of job. A ...