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Besides good predictive performance, the naive Bayesian clas-sifier can also offer a valuable insight into the structure of the training data and effects of the attributes on the class probabilities. This structure may be effectively revealed through visualization of the classifier. We propose a new way to visualize the naive Bayesian model in the form of a(More)
Treatment decisions after diagnosis of clinically localised prostate cancer are difficult due to variability in tumour behaviour. We therefore examined one of the most promising biomarkers in prostate cancer, Ki-67, in a cohort of 808 patients diagnosed with prostate cancer between 1990 and 1996 and treated conservatively. Ki-67 expression was assessed(More)
INTRODUCTION The clinical significance of a treatment effect demonstrated in a randomized trial is typically assessed by reference to differences in event rates at the group level. An alternative is to make individualized predictions for each patient based on a prediction model. This approach is growing in popularity, particularly for cancer. Despite its(More)
New computationally intensive tools for medical survival analyses include recursive patitioning (also called CART) and artificial neural networks. A challenge that remains is to better understand the behavior of these techniques in effort to know when they will be effective tools. Theoretically they may overcome limitations of the traditional multivariable(More)
We previously established the autochthonous transgenic adenocarcinoma mouse prostate (TRAMP) model to facilitate characterization of molecular mechanisms involved in the initiation and progression of prostate cancer. TRAMP mice display high grade prostatic intraepithelial neoplasia or well-differentiated prostate cancer by 10-12 weeks of age. To test the(More)
Machine learning techniques have recently received considerable attention, especially when used for the construction of prediction models from data. Despite their potential advantages over standard statistical methods, like their ability to model non-linear relationships and construct symbolic and interpretable models, their applications to survival(More)
PURPOSE Few published studies have simultaneously analyzed multiple prognostic factors to predict recurrence after surgery for conventional clear cell renal cortical carcinomas. We developed and performed external validation of a postoperative nomogram for this purpose. We used a prospectively updated database of more than 1,400 patients treated at a single(More)
Prostate cancer is the most prevalent cancer in men and predominantly affects older men (aged >or=70 years). The median age at diagnosis is 68 years; overall, two-thirds of prostate cancer-related deaths occur in men aged >or=75 years. With the exponential ageing of the population and the increasing life-expectancy in developed countries, the burden of(More)
Data mining is often used to develop predictive models from data, but rarely addresses how these models are to be employed. To use the constructed model, the user is usually required to run an often complex data mining suite in which the model has been constructed. A better mechanism for the communication of resulting models and less complex, easy to use(More)