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Probabilistic Classifiers Chains (PCC) offers interesting properties to solve multi-label classification tasks due to its ability to estimate the joint probability of the labels. However, PCC presents the major drawback of having a high computational cost in the inference process required to predict new samples. Lately, several approaches have been proposed… (More)
Probabilistic classifier chains have recently gained interest in multi-label classification, due to their ability to optimally estimate the joint probability of a set of labels. The main hindrance is the excessive computational cost of performing inference in the prediction stage. This pitfall has opened the door to propose efficient inference alternatives… (More)
The use of (18)F-DOPA PET/CT with magnetic resonance imaging fusion and the use of visual methods and quantitative analysis helps to differentiate between changes post-radiosurgery vs. suspicion of disease progression in a patient with brain metastases from melanoma, thus facilitating taking early surgical action.
PURPOSE To determine the primary success and recurrence rate of amniotic membrane transplantation (AMT) for the treatment of persistent corneal epithelial defects (PEDs) in eyes after penetrating keratoplasty (PK). DESIGN Retrospective, non-randomized, observational case series. METHOD AMT was performed in 24 eyes of 24 patients with erosions (n=6) or… (More)