Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...
Abstract. In pharmacovigilance, linking the adverse reactions by patients to drugs they took is a key activity typically based on the analysis of patient reports. Yet generating po...
Abstract. Creating computer-interpretable guidelines (CIGs) requires much effort. This effort would be leveraged by sharing CIGs with more than one implementing institution. Sharin...
: Clinical Pathways can be viewed as workflows, comprising an ordering of activities with associated execution constraints. Workflow models allow formal representation, analysis an...
Abstract The volume and complexity of knowledge produced by medical research calls for the development of technology for automated management and analysis of such knowledge. In thi...
Nikos Gorogiannis, Anthony Hunter, Vivek Patkar, M...
Abstract. The paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of Dynamic Contrast-Enhan...
Alessandro Daducci, Umberto Castellani, Marco Cris...
This paper empirically compares six background correction methods aimed at removing unspecific background noise of the overall signal level measured by a scanner across microarrays...
Abstract. Clinical guidelines (GLs) play an important role to standardize and organize clinical processes according to evidence-based medicine. Several computer-based GL representa...
Marco Beccuti, Alessio Bottrighi, Giuliana Frances...
We use the concept of conditional mutual information (MI) to approach problems involving the selection of variables in the area of medical diagnosis. Computing MI requires estimate...
In this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. We quantify the complexity of a biomedical dataset using five complex...