Feature selection is an important task in data mining and machine learning processes. This task is well known in both supervised and unsupervised contexts. The semi-supervised feature selection is still under development and far from being mature. In general, machine learning has been well developed in order to deal with partially-labeled data. Thus, feature selection has obtained special impor...

To establish links between a large number of reviews and events, we propose a web reviews and events matching approach by event feature segments and semi-Markov conditional random fields (CRFs). We extract named entities and verb phrases from reviews as event feature segments. We use semi-Markov CRFs to label the reviews and to recognize event feature segments at the segment level. This approac...

Feature selection is fundamental in many data mining or machine learning applications. Most of the algorithms proposed for this task make the assumption that the data are either supervised or unsupervised, while in practice supervised and unsupervised samples are often simultaneously available. Semi-supervised feature selection is thus needed, and has been studied quite intensively these past f...

Manual identification of structures and features in multidimensional images is at best time consuming and operator dependent. Feature identification need to be accurate, repeatable and quantitative. This thesis presents novel methods for automated feature detection in multidimensional images that are independent on imaging modality. Feature detection is described at two abstraction levels. At t...

BACKGROUND The semi-quantitative serum procalcitonin test (Brahms PCT-Q) is available conveniently in clinical practice. However, there are few data on the relationship between results for this semi-quantitative procalcitonin test and clinical outcomes of community-acquired pneumonia (CAP). We investigated the usefulness of this procalcitonin test for predicting the clinical outcomes of CAP in ...

Laser interstitial thermotherapy (LITT) is a relatively new focal therapy technique for the ablation of localized prostate cancer. In this study, for the first time, we are integrating ex vivo pathology and magnetic resonance imaging (MRI) to assess the imaging characteristics of prostate cancer and treatment changes following LITT. Via a unique clinical trial, which gave us the availability of...