Arrhythmia Detection Using Convolutional Neural Models

Our main goal was studying the effectiveness of transfer learning using 2D CNNs. For this task, we generated spectrograms from ECG segments that were fed to a CNN to automatically extract features. These features are classified by a MLP into arrhythmic or normal rhythm segments, achieving 90% accuracy.Nuestra meta principal consistió en estudiar la efectividad de la transferencia de aprendizaje en el uso de CNNs 2D. Para ello, generamos espectrogramas, a partir de segmentos de electrocardiogramas, que sirvieron como entrada de una CNN para extraer automáticamente sus características. Estas características son clasificadas por un MLP para discernir entre segmentos arrítmicos o normales, obteniendo una precisión del 90%

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis

<smarttagtype namespaceuri="urn:schemas-microsoft-com:office:smarttags" name="City"><smarttagtype namespaceuri="urn:schemas-microsoft-com:office:smarttags" name="place"> Effect of ethanolic extract of root of <i style="">Pongamia pinnata</i> (L) pierre on oxidative stress, behavioral and histopathological alterations induced by cerebral ischemia–reperfusion and long-term hypoperfusion in rats </smarttagtype></smarttagtype>

868-876 Possible effect of an ethanolic root extract of Pongamia pinnata (L) Pierre (P. pinnata) on oxidant-antioxidant status and histopathological changes in acute ischemia-reperfusion injury in the rat forebrain have been investigated. Further, its effect was also assessed on long-term cerebral hypoperfusion-induced changes in anxiety, cognitive and histopathological parameters. Cerebral post-ischemic reperfusion is known to be associated with generation of free radicals. In the present study, bilateral common carotid artery occlusion (BCCAO) for 30 min followed by 45 min reperfusion produced increases in lipid peroxidation, superoxide dismutase (SOD) activity and a fall in the total tissue sulfhydryl (T-SH) levels. The ethanolic extract of roots of P. pinnata (50 mg kg-1, po for 5 days) attenuated the ischemia-reperfusion-induced increase in lipid peroxidation, SOD activity and a fall in T-SH levels. The extract also ameliorated histopathological changes and inflammatory cell infiltration in the frontoparietal region of the rat brain. The extract (50 mg kg-1, po for 15 days) was also found to alleviate the long-term hypoperfusion-induced anxiety and listlessness (open field paradigm). There was an improvement of learning and memory deficits (Morris’ water maze testing). It also attenuated reactive changes in forebrain histology like gliosis, lymphocytic infiltration, astrocytosis and cellular edema. Results suggest protective role of P. pinnata in ischemia-reperfusion injury and cerebrovascular insufficiency states. </smarttagtype

Constraints on off-shell Higgs boson production and the Higgs boson total width in ZZ -> 4l and ZZ -> 2l2v final states with the ATLAS detector

A measurement of off-shell Higgs boson production in the ZZ -> 4l and ZZ -> 2l2v decay channels, where stands for either an electron or a muon, is performed using data from proton-proton collisions at a centre-of-mass energy of root s = 13 TeV. The data were collected by the ATLAS experiment in 2015 and 2016 at the Large Hadron Collider, and they correspond to an integrated luminosity of 36.1 fb(-1). An observed (expected) upper limit on the off-shell Higgs signal strength, defined as the event yield normalised to the Standard Model prediction, of 3.8 (3.4) is obtained at 95% confidence level (CL). Assuming the ratio of the Higgs boson couplings to the Standard Model predictions is independent of the momentum transfer of the Higgs production mechanism considered in the analysis, a combination with the on-shell signal-strength measurements yields an observed (expected) 95% CL upper limit on the Higgs boson total width of 14.4 (15.2) MeV. (C) 2018 The Author. Published by Elsevier B.V