6 research outputs found

    Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals

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    Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by grouping patients according to clinical characteristics. Based on neural network techniques, our objective was to identify those factors for HIV/HCV co-infected patients (to which clinicians have given careful consideration before treatment uptake) that have not being included among the prioritisation criteria. This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. An evolutionary algorithm was used to determine the architecture and estimate the coefficients of the model. This machine learning methodology found that radial basis neural networks provided a very simple model in terms of the number of patient characteristics to be considered by the classifier (in this case, six), returning a good overall classification accuracy of 0.767 and a minimum sensitivity (for the classification of the minority class, untreated patients) of 0.550. Finally, the area under the ROC curve was 0.802, which proved to be exceptional. The parsimony of the model makes it especially attractive, using just eight connections. The independent variable "recent PWID" is compulsory due to its importance. The simplicity of the model means that it is possible to analyse the relationship between patient characteristics and the probability of belonging to the treated group

    Vocabulario de la sociedad civil, la ruralidad y los movimientos sociales en América Latina

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    El Vocabulario de la Sociedad Civil, la Ruralidad y los Movimientos Sociales en América Latina tiene como objetivo desarrollar vocablos relacionados con temas de gran trascendencia para la vida colectiva de la población Latinoamericana; pretende introducir a estudiantes, personas del ámbito académico y activistas en la comprensión de estas categorías de análisis. A través de la mirada de 70 especialistas que participaron en este vocabulario, es posible comprender muchos de los términos que se utilizan dentro de la investigación social y áreas relacionadas con las ciencias políticas, ambientales y rurales, a partir de una mayor explicación y detalle. Es por ello que se inserta este trabajo desde una mirada colectiva y amplia de los conceptos que se exponen. En este libro podrá encontrar las ideas de varios autores y autoras de distintas universidades, con una visión multi, inter y transdisciplinaria. El esfuerzo que se realizó para conjuntar varios términos y analizar su compleja red de interpretaciones, permitirá que este manuscrito pueda ser consultado por estudiantes, personas del ámbito científico-académico, y ciudadanía; porque contiene el estado del arte, la historia del paulatino avance de múltiples conceptos y su vigencia en el contexto actual

    Biological and prognostic differences between symptomatic colorectal carcinomas and those detected by screening

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    Constraining the magnitude of the Chiral Magnetic Effect with Event Shape Engineering in Pb-Pb collisions at sNN\sqrt{s_{\rm NN}} = 2.76$ TeV

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    In ultrarelativistic heavy-ion collisions, the event-by-event variation of the elliptic flow v2v_2 reflects fluctuations in the shape of the initial state of the system. This allows to select events with the same centrality but different initial geometry. This selection technique, Event Shape Engineering, has been used in the analysis of charge-dependent two- and three-particle correlations in Pb-Pb collisions at sNN=2.76\sqrt{s_{_{\rm NN}}} =2.76 TeV. The two-particle correlator cos(φαφβ)\langle \cos(\varphi_\alpha - \varphi_\beta) \rangle, calculated for different combinations of charges α\alpha and β\beta, is almost independent of v2v_2 (for a given centrality), while the three-particle correlator cos(φα+φβ2Ψ2)\langle \cos(\varphi_\alpha + \varphi_\beta - 2\Psi_2) \rangle scales almost linearly both with the event v2v_2 and charged-particle pseudorapidity density. The charge dependence of the three-particle correlator is often interpreted as evidence for the Chiral Magnetic Effect (CME), a parity violating effect of the strong interaction. However, its measured dependence on v2v_2 points to a large non-CME contribution to the correlator. Comparing the results with Monte Carlo calculations including a magnetic field due to the spectators, the upper limit of the CME signal contribution to the three-particle correlator in the 10-50% centrality interval is found to be 26-33% at 95% confidence level
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