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Paulo J. G. Lisboa: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Abir Jaafar Hussain, Adam Knowles, Paulo J. G. Lisboa, Wael El-Deredy, Dhiya Al-Jumeily
    Polynomial Pipelined Neural Network and Its Application to Financial Time Series Prediction. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2006, pp:597-606 [Conf]
  2. Terence A. Etchells, Àngela Nebot, Alfredo Vellido, Paulo J. G. Lisboa, Francisco Mugica
    Learning what is important: feature selection and rule extraction in a virtual course. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:401-406 [Conf]
  3. Alfredo Vellido, Paulo J. G. Lisboa
    Functional topographic mapping for robust handling of outliers in brain tumour data. [Citation Graph (0, 0)][DBLP]
    ESANN, 2005, pp:133-138 [Conf]
  4. Alfredo Vellido, Paulo J. G. Lisboa, Dolores Vicente
    Handling outliers and missing data in brain tumour clinical assessment using t-GTM. [Citation Graph (0, 0)][DBLP]
    ESANN, 2005, pp:121-126 [Conf]
  5. Paulo J. G. Lisboa, Shail Patel
    Cluster-Based Visualisation of Marketing Data. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2004, pp:552-558 [Conf]
  6. A. Agogino, Joydeep Ghosh, Stavros J. Perantonis, Vassilis Virvilis, Sergios Petridis, Paulo J. G. Lisboa
    The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data. [Citation Graph (0, 0)][DBLP]
    IJCNN (3), 2000, pp:47-52 [Conf]
  7. Alfredo Vellido, Paulo J. G. Lisboa, Karon Meehan
    Segmenting the e-Commerce Market Using the Generative Topographic Mapping. [Citation Graph (0, 0)][DBLP]
    MICAI, 2000, pp:470-481 [Conf]
  8. Shail Patel, O. Bataveljic, Paulo J. G. Lisboa, C. Hawkins, R. Rajan
    iShakti - Crossing the Digital Divide in Rural India. [Citation Graph (0, 0)][DBLP]
    Web Intelligence, 2006, pp:1061-1065 [Conf]
  9. V. S. Kodogiannis, Paulo J. G. Lisboa, J. Lucas
    Neural network modelling and control for underwater vehicles. [Citation Graph (0, 0)][DBLP]
    AI in Engineering, 1996, v:10, n:3, pp:203-212 [Journal]
  10. Paulo J. G. Lisboa, H. Wong, P. Harris, R. Swindell
    A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2003, v:28, n:1, pp:1-25 [Journal]
  11. K. Glossop, Paulo J. G. Lisboa, P. C. Russell, A. Siddans, G. R. Jones
    An Implementation of the Hough Transformation for the Identification and Labelling of Fixed Period Sinusoidal Curves. [Citation Graph (0, 0)][DBLP]
    Computer Vision and Image Understanding, 1999, v:74, n:1, pp:96-100 [Journal]
  12. José David Martín-Guerrero, Paulo J. G. Lisboa, Emilio Soria-Olivas, Alberto Palomares, Emili Balaguer
    An approach based on the Adaptive Resonance Theory for analysing the viability of recommender systems in a citizen Web portal. [Citation Graph (0, 0)][DBLP]
    Expert Syst. Appl., 2007, v:33, n:3, pp:743-753 [Journal]
  13. Alfredo Vellido, Paulo J. G. Lisboa, Karon Meehan
    The generative topographic mapping as a principal model for data visualization and market segmentation: an electronic commerce case. [Citation Graph (0, 0)][DBLP]
    Int. J. Comput. Syst. Signal, 2000, v:1, n:2, pp:119-138 [Journal]
  14. Paulo J. G. Lisboa, Terence A. Etchells, Dave C. Pountney
    Minimal MLPs do not model the XOR logic. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:48, n:1-4, pp:1033-1037 [Journal]
  15. Alfredo Vellido, Paulo J. G. Lisboa, Dolores Vicente
    Robust analysis of MRS brain tumour data using t-GTM. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:69, n:7-9, pp:754-768 [Journal]
  16. Andreas Lindemann, Christian L. Dunis, Paulo J. G. Lisboa
    Level estimation, classification and probability distribution architectures for trading the EUR/USD exchange rate. [Citation Graph (0, 0)][DBLP]
    Neural Computing and Applications, 2005, v:14, n:3, pp:256-271 [Journal]
  17. Alfredo Vellido, Paulo J. G. Lisboa
    An Electronic Commerce Application of the Bayesian Framework for MLPs: The Effect of Marginalisation and ARD. [Citation Graph (0, 0)][DBLP]
    Neural Computing and Applications, 2001, v:10, n:1, pp:3-11 [Journal]
  18. Paulo J. G. Lisboa
    A review of evidence of health benefit from artificial neural networks in medical intervention. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2002, v:15, n:1, pp:11-39 [Journal]
  19. Paulo J. G. Lisboa, Alfredo Vellido, H. Wong
    Bias reduction in skewed binary classification with Bayesian neural networks. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2000, v:13, n:4-5, pp:407-410 [Journal]
  20. M. S. H. Aung, Paulo J. G. Lisboa, Terence A. Etchells, A. C. Testa, Ben Van Calster, Sabine Van Huffel, L. Valentin, Dirk Timmerman
    Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy. [Citation Graph (0, 0)][DBLP]
    ISNN (2), 2007, pp:1177-1186 [Conf]
  21. Alfredo Vellido, Paulo J. G. Lisboa
    Neural Networks and Other Machine Learning Methods in Cancer Research. [Citation Graph (0, 0)][DBLP]
    IWANN, 2007, pp:964-971 [Conf]
  22. Paulo J. G. Lisboa, Ian H. Jarman, Terence A. Etchells, Phillip Ramsey
    A Prototype Integrated Decision Support System for Breast Cancer Oncology. [Citation Graph (0, 0)][DBLP]
    IWANN, 2007, pp:996-1003 [Conf]

  23. Evaluating Retail Recommender Systems via Retrospective Data: Lessons Learnt from a Live-Intervention Study. [Citation Graph (, )][DBLP]


  24. Machine learning in cancer research: implications for personalised medicine. [Citation Graph (, )][DBLP]


  25. Classification, Dimensionality Reduction, and Maximally Discriminatory Visualization of a Multicentre 1H-MRS Database of Brain Tumors. [Citation Graph (, )][DBLP]


  26. Missing Data Imputation in Longitudinal Cohort Studies: Application of PLANN-ARD in Breast Cancer Survival. [Citation Graph (, )][DBLP]


  27. External Validation of a Bayesian Neural Network Model in Survival Analysis. [Citation Graph (, )][DBLP]


  28. A Clinical Decision Support System for Breast Cancer Patients. [Citation Graph (, )][DBLP]


  29. Assessing flexible models and rule extraction from censored survival data. [Citation Graph (, )][DBLP]


  30. Time-to-event analysis with artificial neural networks: An integrated analytical and rule-based study for breast cancer. [Citation Graph (, )][DBLP]


  31. An adaptive hybrid image compression method and its application to medical images. [Citation Graph (, )][DBLP]


  32. Stratification Methodologies for Neural Networks Models of Survival. [Citation Graph (, )][DBLP]


  33. Grocery shopping recommendations based on basket-sensitive random walk. [Citation Graph (, )][DBLP]


  34. Stratification of Severity of Illness Indices: A Case Study for Breast Cancer Prognosis. [Citation Graph (, )][DBLP]


  35. Are Model-Based Clustering and Neural Clustering Consistent? A Case Study from Bioinformatics. [Citation Graph (, )][DBLP]


  36. The value of personalised recommender systems to e-business: a case study. [Citation Graph (, )][DBLP]


  37. A probabilistic model for item-based recommender systems. [Citation Graph (, )][DBLP]


  38. Different Methodologies for Patient Stratification Using Survival Data. [Citation Graph (, )][DBLP]


  39. An Adaptive Hybrid Classified Vector Quantisation and its Application to Image Compression. [Citation Graph (, )][DBLP]


  40. An integrated framework for risk profiling of breast cancer patients following surgery. [Citation Graph (, )][DBLP]


  41. How to find simple and accurate rules for viral protease cleavage specificities. [Citation Graph (, )][DBLP]


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