Social Business Intelligence (SBI) enables companies to capture strategic information from public social networks. Contrary to traditional Business Intelligence (BI), SBI has to face the high ...dynamicity of both the social network’s contents and the company’s analytical requests, as well as the enormous amount of noisy data. Effective exploitation of these continuous sources of data requires efficient processing of the streamed data to be semantically shaped into insightful facts. In this paper, we propose a multidimensional formalism to represent and evaluate social indicators directly from fact streams derived in turn from social network data. This formalism relies on two main aspects: the semantic representation of facts via Linked Open Data and the support of OLAP-like multidimensional analysis models. Contrary to traditional BI formalisms, we start the process by modeling the required social indicators according to the strategic goals of the company. From these specifications, all the required fact streams are modeled and deployed to trace the indicators. The main advantages of this approach are the easy definition of on-demand social indicators, and the treatment of changing dimensions and metrics through streamed facts. We demonstrate its usefulness by introducing a real scenario user case in the automotive sector.
Although diffuse alveolar damage (DAD) is considered the typical histological pattern of acute respiratory distress syndrome (ARDS), only half of patients exhibit this morphological hallmark. ...Patients with DAD may have higher mortality than those without DAD. Therefore, we aimed to identify the factors associated with DAD in patients with ARDS.
We analyzed autopsy samples of 356 patients who had ARDS at the time of death. DAD was assessed by two pathologists, and ARDS criteria were evaluated by two intensivists. Criteria for severe ARDS included the degree of hypoxemia and the ancillary variables of the current Berlin definition assessed within 48 h before death: radiographic severity, high positive end-expiratory pressure (PEEP) level, and physiological variables (i.e., altered respiratory system compliance and large anatomic dead space).
After multivariable analysis, high PEEP levels, physiological variables, and opacities involving only three quadrants on chest radiographs were not associated with DAD. The four markers independently associated with DAD were (1) duration of evolution (OR 3.29 1.95-5.55 for patients with ARDS ≥ 3 days, p < 0.001), (2) degree of hypoxemia (OR 3.92 1.48-10.3 for moderate ARDS and 6.18 2.34-16.3 for severe ARDS, p < 0.01 for both), (3) increased dynamic driving pressure (OR 1.06 1.04-1.09, p = 0.007), and (4) radiographic severity (OR 2.91 1.47-5.75 for patients with diffuse opacities involving the four quadrants, p = 0.002). DAD was found in two-thirds of patients with a ratio of partial pressure of arterial oxygen to fraction of inspired oxygen ≤ 100 mmHg and opacities involving the four quadrants.
In addition to severe hypoxemia, diffuse opacities involving the four quadrants were a strong marker of DAD.
Research in the Life Sciences depends on the integration of large, distributed and heterogeneous web resources (e.g., data sources and web services). The discovery of which of these resources are the ...most appropriate to solve a given task is a complex research question, since there are many candidate resources and there is little, mostly unstructured, metadata to be able to decide among them. In this paper, we contribute to a semi-automatic approach, based on semantic techniques, to assist researchers in the discovery of the most appropriate web resources to fulfill a set of requirements. The main feature of our approach is that it exploits broad knowledge resources in order to annotate the unstructured texts that are available in the emerging web-based repositories of web resource metadata. The results show that the web resource discovery process benefits from a semantic-based approach in several important aspects. One of the advantages is that the user can express her requirements in natural language avoiding the use of specific vocabularies or query languages. Moreover, the discovery exploits not only the categories or tags of web resources, but also their description and documentation.
The aim of this transversal study was to describe the virological and immunological features of HIV-infected youths transferred from pediatric to adult care units since 1997 vs. the non-transferred ...patients from the Madrid Cohort of HIV-infected children and adolescents in Spain. We included 106 non-transferred and 184 transferred patients under clinical follow-up in 17 public hospitals in Madrid by the end of December 2017. Virological and immunological outcomes were compared in transferred vs. non-transferred patients. ART drug resistance mutations and HIV-variants were analyzed in all subjects with available resistance pol genotypes and/or genotypic resistance profiles. Among the study cohort, 133 (72.3%) of 184 transferred and 75 (70.7%) of 106 non-transferred patients had available resistance genotypes. Most (88.9%) of transferred had ART experience at sampling. A third (33.3%) had had a triple-class experience. Acquired drug resistance (ADR) prevalence was significantly higher in pretreated transferred than non-transferred patients (71.8% vs. 44%; p = 0.0009), mainly to NRTI (72.8% vs. 31.1%; p < 0.0001) and PI (29.1% vs. 12%; p = 0.0262). HIV-1 non-B variants were less frequent in transferred vs. non-transferred (6.9% vs. 32%; p < 0.0001). In conclusion, the frequent resistant genotypes found in transferred youths justifies the reinforcement of HIV resistance monitoring after the transition to avoid future therapeutic failures.
To determine the frequency of breast cancer (BC) patients with hereditary risk features in a wide retrospective cohort of patients in Spain.
a retrospective analysis was conducted from 10,638 BC ...patients diagnosed between 1998 and 2001 in the GEICAM registry "El Álamo III", dividing them into four groups according to modified ESMO and SEOM hereditary cancer risk criteria: Sporadic breast cancer group (R0); Individual risk group (IR); Familial risk group (FR); Individual and familial risk group (IFR) with both individual and familial risk criteria.
7,641 patients were evaluable. Of them, 2,252 patients (29.5%) had at least one hereditary risk criteria, being subclassified in: FR 1.105 (14.5%), IR 970 (12.7%), IFR 177 (2.3%). There was a higher frequency of newly diagnosed metastatic patients in the IR group (5.1% vs 3.2%, p = 0.02). In contrast, in RO were lower proportion of big tumors (> T2) (43.8% vs 47.4%, p = 0.023), nodal involvement (43.4% vs 48.1%, p = 0.004) and lower histological grades (20.9% G3 for the R0 vs 29.8%) when compared to patients with any risk criteria.
Almost three out of ten BC patients have at least one hereditary risk cancer feature that would warrant further genetic counseling. Patients with hereditary cancer risk seems to be diagnosed with worse prognosis factors.
The tremendous popularity of web-based social media is attracting the attention of the industry to take profit from the massive availability of sentiment data, which is considered of a high value for ...Business Intelligence (BI). So far, BI has been mainly concerned with corporate data with little or null attention to the external world. However, for BI analysts, taking into account the Voice of the Customer (VoC) and the Voice of the Market (VoM) is crucial to put in context the results of their analyses. Recent advances in Sentiment Analysis have made possible to effectively extract and summarize sentiment data from these massive social media. As a consequence, VoC and VoM can be now listened from web-based social media (e.g., blogs, reviews forums, social networks, and so on). However, new challenges arise when attempting to integrate traditional corporate data and external sentiment data. This paper deals with these issues and proposes a novel semantic data infrastructure for BI aimed at providing new opportunities for integrating traditional and social BI. This infrastructure follows the principles of the Linked Open Data initiative.
Web opinion feeds have become one of the most popular information sources users consult before buying products or contracting services. Negative opinions about a product can have a high impact in its ...sales figures. As a consequence, companies are more and more concerned about how to integrate opinion data in their business intelligence models so that they can predict sales figures or define new strategic goals. After analysing the requirements of this new application, this paper proposes a multidimensional data model to integrate sentiment data extracted from opinion posts in a traditional corporate data warehouse. Then, a new sentiment data extraction method that applies semantic annotation as a means to facilitate the integration of both types of data is presented. In this method, Wikipedia is used as the main knowledge resource, together with some well-known lexicons of opinion words and other corporate data and metadata stores describing the company products like, for example, technical specifications and user manuals. The resulting information system allows users to perform new analysis tasks by using the traditional OLAP-based data warehouse operators. We have developed a case study over a set of real opinions about digital devices which are offered by a wholesale dealer. Over this case study, the quality of the extracted sentiment data is evaluated, and some query examples that illustrate the potential uses of the integrated model are provided.
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