Transductive Label Augmentation for Improved Deep Network Learning

A major impediment to the application of deep learning to real-world problems is the scarcity of labeled data. Small training sets are in fact of no use to deep networks as, due to the large number of trainable parameters, they will very likely be subject to overfitting phenomena. On the other hand, the increment of the training set size through further manual or semi-automatic labellings can be costly, if not possible at times. Thus, the standard techniques to address this issue are transfer learning and data augmentation, which consists of applying some sort of "transformation" to existing labeled instances to let the training set grow in size. Although this approach works well in applications such as image classification, where it is relatively simple to design suitable transformation operators, it is not obvious how to apply it in more structured scenarios. Motivated by the observation that in virtually all application domains it is easy to obtain unlabeled data, in this paper we take a different perspective and propose a \emph{label augmentation} approach. We start from a small, curated labeled dataset and let the labels propagate through a larger set of unlabeled data using graph transduction techniques. This allows us to naturally use (second-order) similarity information which resides in the data, a source of information which is typically neglected by standard augmentation techniques. In particular, we show that by using known game theoretic transductive processes we can create larger and accurate enough labeled datasets which use results in better trained neural networks. Preliminary experiments are reported which demonstrate a consistent improvement over standard image classification datasets.Comment: Accepted on IEEE International Conference on Pattern Recognitio

Revascularization for coronary artery disease in diabetes mellitus: Angioplasty, stents and coronary artery bypass grafting

Author Manuscript: 2011 April 14Patients with diabetes mellitus (DM) are prone to a diffuse and rapidly progressive form of atherosclerosis, which increases their likelihood of requiring revascularization. However, the unique pathophysiology of atherosclerosis in patients with DM modifies the response to arterial injury, with profound clinical consequences for patients undergoing percutaneous coronary intervention (PCI). Multiple studies have shown that DM is a strong risk factor for restenosis following successful balloon angioplasty or coronary stenting, with greater need for repeat revascularization and inferior clinical outcomes. Early data suggest that drug eluting stents reduce restenosis rates and the need for repeat revascularization irrespective of the diabetic state and with no significant reduction in hard clinical endpoints such as myocardial infarction and mortality. For many patients with 1- or 2-vessel coronary artery disease, there is little prognostic benefit from any intervention over optimal medical therapy. PCI with drug-eluting or bare metal stents is appropriate for patients who remain symptomatic with medical therapy. However, selection of the optimal myocardial revascularization strategy for patients with DM and multivessel coronary artery disease is crucial. Randomized trials comparing multivessel PCI with balloon angioplasty or bare metal stents to coronary artery bypass grafting (CABG) consistently demonstrated the superiority of CABG in patients with treated DM. In the setting of diabetes CABG had greater survival, fewer recurrent infarctions or need for re-intervention. Limited data suggests that CABG is superior to multivessel PCI even when drug-eluting stents are used. Several ongoing randomized trials are evaluating the long-term comparative efficacy of PCI with drug-eluting stents and CABG in patients with DM. Only further study will continue to unravel the mechanisms at play and optimal therapy in the face of the profoundly virulent atherosclerotic potential that accompanies diabetes mellitus.National Institutes of Health (U.S.) (GM 49039

Coper mineralizations related to volcano-sedimentary formation in the Albanian ophiolites periphery

111-117 pConsiglio Nazionale delle Ricerche (CNR). Biblioteca Centrale / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

Factors affecting the prognosis of Albanian adult patients with generalized tetanus

Background. Despite systematic vaccination of the population, tetanus continues to be a health problem in Albania, as in some other developing countries. In this study, our intent was to evaluate prognostic factors relating to death in adult patients with generalized tetanus. Methodology and patients. All the patients (60) included in the study were hospitalized at the regional hospitals of Shkodra and Korça, and the University Hospital Centre “Mother Theresa” of Tirana, Albania, during the period of 1984-2004. They had a mean age of 49.1+14.4 years, 43 (71.7%) were males and 40 (66.6%) of them lived in rural areas. The mean incubation period was 12 days and the case-fatality rate (CFR) was 38.3%. Results. The CFR in patients with an onset period ≥2 days was 21.7% and in those with 50 years old had a CFR=60.87% (OR=7, p 120 beats/min, and hypertension. Discussion. The main prognostic factor of those analyzed in our study appeared to be the onset period and the age of the patients. We didn’t find significant differences in CFR in patients with different incubation periods. Clinicians must take into account that wound complication and localization, tachycardia and hypertension, high fever, male gender and urban residency significantly influence the prognoses of adults with generalized tetanus