This work investigates variable selection and classification for biomedical datasets with a small sample size and a very high input dimension. The sequential sparse Bayesian learning methods with linear bases are used as ...

Background. To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, ...

OBJECTIVE: To assess the impact of the introduction of an ultrasound-based model of care for women with acute gynecological complications. METHODS: This was a prospective comparative study of women attending an ultrasound-based ...

PURPOSE: To prospectively test the mathematical models for calculation of the risk of malignancy in adnexal masses that were developed on the International Ovarian Tumor Analysis (IOTA) phase 1 data set on a new data set ...