1,795 research outputs found

    COVID-19 Mortality Risk Prediction Using X-Ray Images

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    The pandemic caused by coronavirus COVID-19 has already had a massive impact in our societies in terms of health, economy, and social distress. One of the most common symptoms caused by COVID-19 are lung problems like pneumonia, which can be detected using X-ray images. On the other hand, the popularity of Machine Learning models has grown exponentially in recent years and Deep Learning techniques have become the state-of-the-art for image classification tasks and is widely used in the healthcare sector nowadays as support for clinical decisions. This research aims to build a prediction model based on Machine Learning, including Deep Learning, techniques to predict the mortality risk of a particular patient given an X-ray and some basic demographic data. Keeping this in mind, this paper has three goals. First, we use Deep Learning models to predict the mortality risk of a patient based on this patient X-ray images. For this purpose, we apply Convolutional Neural Networks as well as Transfer Learning techniques to mitigate the effect of the reduced amount of COVID19 data available. Second, we propose to combine the prediction of this Convolutional Neural Network with other patient data, like gender and age, as input features of a final Machine Learning model, that will act as second and final layer. This second model layer will aim to improve the goodness of fit and prediction power of our first layer. Finally, and in accordance with the principle of reproducible research, the data used for the experiments is publicly available and we make the implementations developed easily accessible via public repositories. Experiments over a real dataset of COVID-19 patients yield high AUROC values and show our two-layer framework to obtain better results than a single Convolutional Neural Network (CNN) model, achieving close to perfect classification

    Misbehaviors of Front-Line Research Personnel and the Integrity of Community-Based Research

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    There has been little empirical research into misconduct and misbehavior among community research workers who recruit and collect data in vulnerable and marginalized health populations and are also members of those same communities. We conducted qualitative interviews with community research workers and traditional research assistants to understand the context and consequences of misbehaviors that pose a threat to research ethics and data integrity. In our sample, more community research workers acknowledged engaging in research wrongdoing than did traditional research assistants. These behaviors were most prevalent among community research workers who were not well-integrated into the research team. We suggest best practices for investigators to promote an environment that supports research integrity in research projects that employ community research workers

    Problematique De L\'utilisation Des Engrais Mineraux Dans Les Zones De Production Du Riz : Cas Du Centre-Ouest De La Côte D\'ivoire

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    Dans le but de mettre au point de barèmes de fumure minérale adaptés aux régions et aux variétés nouvelles de riz pluvial, une enquête a été réalisée à Saïoua, auprès de 7 associations de riziculteurs dans le Centre Ouest de la Côte d\'Ivoire. Cette enquête a porté sur les riziculteurs et leur environnement, les caractéristiques des systèmes de culture à base de riz pluvial, la perception et l\'utilisation des engrais chimiques et, enfin, la destination de la production rizicole. Il ressort de l\'enquête que la production de riz est à dominance destinée à l\'autoconsommation. La riziculture pluviale, activité la plus répandue dans la région, est pratiquée à 95 % par les femmes. Elle demeure encore itinérante, avec apparition, localisée de zones de blocage foncier. Cette situation a entraîné l\'éloignement des parcellesrizicoles des villages et une exploitation continue de certaines parcelles pendant 2, voire 3 ans. les pratiques agricolesont entrainé la nécessité de de restaurer les terres cultivées à travers l\'utilisation des engrais chimiques selon les paysans. Aussi, le souhait des trois quarts des riziculteurs enquêtés est-il d\'utiliser ces engrais chimiques. Mais, compte tenu du coût élevé et de la faiblesse du pouvoir d\'achat de la population rurale, les engrais ne sont pas effectivement utilisés. Les quelques riziculteurs enquêtés, qui ont déjà utilisés les engrais chimiques, ont obtenu les produits par le biais d\'Organisations Non Gouvernementales (ONG) à la faveur de projets agricoles.In order to define appropriate fertilizer rates for new rice varieties in the different areas of rainfed rice production, a survey was conducted in Saïoua, mid-west Côte d\'Ivoire. Seven rice farmer associations were surveyed. Parameters, such as: upland rice-based systems and market chracteristics,as well as farmer social status and perceptions toward mineral fertilizer use were assessed. Results show that : 95 % of rice farmers were women and cropping systems itinerant. This led to land scarcity, remoteness of production sites with respect to thomes, as well as land overuse (3-4 years of continuous cropping on the same land). Mineral fertilizer addition to soil appears to be the solution to this problem. For most farmers (75%), beside fallows systems, chemical fertilizer additions appear to be the only way out to improve soil quality. However, because of high chemical fertilizers cost, which is often out of reach of most farmers, fertilizers are not properly used by farmers and production is aimed at self-consumption. The few farmers who used fertilizers in their plots obtained those amendements from local NGOs through agricultural projects implemented in the area. Keywords: riziculture pluviale, enquête, engrais chimiques, Côte d\'Ivoire.Agronomie Africaine Vol. 19 (2) 2007: pp. 173-18

    Polymorphismes du gène ABCB1 (MDR1) et impacts fonctionnels dans le transport de xénobiotiques - Particularités chez les sujets Noirs Subsahariens

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    Les différences interindividuelles observées dans la réponse aux médicaments sont en partie dues aux polymorphismes du gène ABCB1 codant pour la glycoprotéine-P (P-gp), une protéine de transport des médicaments. Cette revue a pour but de faire le point des connaissances sur les polymorphismes du gène ABCB1, leur relevance fonctionnelle et clinique et de préciser les particularités au sein de la population noire subsharienne. Le rôle du gène (ABCB1)MDR1 dans la variabilité pharmacocinétique ou pharmacodynamique a été démontrée clairement in vitro, dans des modèles animaux et lors d’études cliniques. Le polymorphisme C3435T est associé à une diminution de l’expression protéique de la P-gp et, par voie de conséquence, de son activité. L’existence d’une forte association entre les polymorphismes C3435T et G2677T a suggéré alors que la différence fonctionnelle observée peut être attribuée également au deuxième polymorphisme i.e le G2677T (exon 21). Il a été identifié chez les noirs africains de nouveaux polymorphismes et des haplotypes particuliers. Différnts travaux ont démontré également que le gène ABCB1 intervient dans le suivi thérapeutique des patients mis sous immunosuppresseurs, anticancéreux, antidépresseurs, antirétroviraux ou antihypertenseurs. Des perspectives fort intéressantes en pharmacothérapie avec entre autres l’utilisation de modulateurs de la P-gp sont d’actualité.Mots clés: Pharmacogénétique, glycoprotéine-P, médicaments, substances exogènes, Noirs Subsaharien

    Sentimental Analysis of Social Media Using R language and Hadoop

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    The way of expressing people’s views, opinions and Sentiments about others has been changed due to the growth of Technology of World Wide Web. Mostly people use blogs, Social sites, online discussions etc. for expressing their views. Massive amount of data is generated because of this. Companies face many problems in storing this massive data. This paper helps in analysis of sentiments of the data fetched from twitter using R language which either collects the information in the form of positive, negative or neutral score. After this the fetched data is pre-processed i.e. all the slang words, misspelled words etc. are removed. Using R language and Hadoop Connector we perform the analysis of twitter data which has size of TB’s also known as big data. R language and Hadoop tool are the two different platforms on which the performance estimation will be based on

    Variation in upper thermal tolerance among 19 species from temperate wetlands

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    Communities usually possess a multitude of interconnected trophic interactions within food webs. Their regulation generally depends on a balance between bottom-up and top-down effects. However, if sensitivity to temperature varies among species, rising temperatures may change trophic interactions via direct and indirect effects. We examined the critical thermal maximum (CTmax) of 19 species from temperate wetlands (insect predators, amphibian larvae, zooplankton and amphipods) and determined if they vary in their sensitivity to warming temperatures. CTmax differed between the groups, with predatory insects having higher CTmax than amphibians (both herbivorous larval anurans and predatory larval salamanders), amphipods and zooplankton. In a scenario of global warming, these differences in thermal tolerance may affect top-down and bottom-up processes, particularly considering that insect predators are more likely to maintain or improve their performance at higher temperatures, which could lead to increased predation rates on the herbivores in the food web. Further studies are needed to understand how the energy flows through communities, how species’ energy budgets may change and whether other physiological and behavioral responses (such as phenotypic plasticity and thermoregulation) can buffer or increase these changes in the top-down regulation of wetland food webs.U.S. National Science Foundation 0716149Ministerio de Ciencia e Innovación CGL2009-12767-C02-02Ministerio de Economía y Competitividad CGL201240246C0201, CGL2017-86924-
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