Utility of enhanced CT for patients with suspected uncomplicated renal colic and no acute findings on non-enhanced CT

AIM: To evaluate the utility of contrast-enhanced computed tomography (CECT) for patients with suspected uncomplicated renal colic (URC) and no abnormalities on non-enhanced computed tomography (NECT). MATERIALS AND METHODS: The hospital institutional review board and ethics committee approved this retrospective study with a waiver of informed consent. Between January 2016 and April 2017, all consecutive adult patients who consulted at the adult Emergency Department (ED) with suspected URC and who had undergone both NECT and CECT were included retrospectively. The primary endpoint was prevalence of CECT-only diagnosis without acute findings on NECT. The risk factors for an acute finding were identified by logistic regression analysis. RESULTS: Among 126 patients with suspected URC, 12 were excluded. Among the 76 patients with no acute findings on NECT, CECT led to find acute lesions in 14/76 (18%) cases, but only 2/76 (3%) resulted in a change of management. Predictive factors of abnormal finding on CECT were: low renal clearance and high leukocyte count with OR 0.96 (95% confidence interval [CI]: 0.93-0.99), p=0.0189 and OR 5.79 (95% CI: 1.55-21.64), p=0.0091, respectively. CONCLUSIONS: In most cases, NECT is sufficient for screening patients with suspected URC. If leucocytosis and low renal function are present, stronger consideration may be given to CECT

Ontology Enrichment by Discovering Multi-Relational Association Rules from Ontological Knowledge Bases

International audienceIn the Semantic Web context, OWL ontologies represent the con-ceptualization of domains of interest while the corresponding as-sertional knowledge is given by the heterogeneous Web resources referring to them. Being strongly decoupled, ontologies and assertion can be out-of-sync. An ontology can be incomplete, noisy and sometimes inconsistent with regard to the actual usage of its conceptual vocabulary in the assertions. Data mining can support the discovery of hidden knowledge patterns in the data, to enrich the ontologies. We present a method for discovering multi-relational association rules, coded in SWRL, from ontological knowledge bases. Unlike state-of-the-art approaches, the method is able to take the intensional knowledge into account. Furthermore, since discovered rules are represented in SWRL, they can be straightforwardly integrated within the ontology, thus (i) enriching its expressive power and (ii) augmenting the assertional knowledge that can be derived. Discovered rules may also suggest new axioms to be added to the ontology. We performed experiments on publicly available ontologies validating the performances of our approach

Conservation et introduction de lémuriens sur l'îlot Mbouzy (Mayotte)

À Mayotte, l'îlot Mbouzi est un lieu remarquable par son milieu naturel en grande partie préservé, alors qu'il se situe à proximité de la ville principale, Mamoudzou. Il fait l'objet d'une demande de classement en réserve naturelle. Nous pensons utile d'apporter quelques éléments pouvant servir à la réflexion sur l'avenir de cet îlot, et d'établir une sorte d'état des lieux concernant son intérêt biologique. Quelles sont les possibilités d'équilibre à long terme entre les populations animales et végétales, sachant qu'une association (loi de 1901) consacr

Conservation et introduction de lémuriens sur l'îlot Mbouzy (Mayotte)

À Mayotte, l'îlot Mbouzi est un lieu remarquable par son milieu naturel en grande partie préservé, alors qu'il se situe à proximité de la ville principale, Mamoudzou. Il fait l'objet d'une demande de classement en réserve naturelle. Nous pensons utile d'apporter quelques éléments pouvant servir à la réflexion sur l'avenir de cet îlot, et d'établir une sorte d'état des lieux concernant son intérêt biologique. Quelles sont les possibilités d'équilibre à long terme entre les populations animales et végétales, sachant qu'une association (loi de 1901) consacr

Interoperable AI: Evolutionary Race Towards Sustainable Knowledge Sharing

Article and Supplementary MaterialInternational audienceThe advancement and deployment of artificial intelligent agents brought numerous benefits in knowledge and data gathering and processing. However, one of the key challenges in deploying such agents in an open environment like the Web is their interoperability as they currently mostly run in silos. In this paper we report on a simulation and evaluation based on evolutionary agent-based modelling to empirically test how sustainable different strategies are for knowledge sharing in open multi-agent systems (MAS). Our results show the importance of translation-based approaches and the need for incentives to support these

Towards a representation of uncertain geospatial information in knowledge graphs

International audienceThis paper highlights the challenges of representing uncertain geospatial information in knowledge graphs. We propose to use Real Estate advertisements since professionals use a lot of vernacular and vague places in order to promote a house to their target audience. Then, we suggest to model local place names using fuzzy set theory. Finally, we discuss how to build a knowledge graph that represents extracted geospatial objects and their uncertainty. CCS CONCEPTS • Information systems → Geographic information systems

Testing OWL Axioms against RDF Facts: A Possibilistic Approach

International audienceAutomatic knowledge base enrichment methods rely criti-cally on candidate axiom scoring. The most popular scoring heuristics proposed in the literature are based on statistical inference. We argue that such a probability-based framework is not always completely satis-factory and propose a novel, alternative scoring heuristics expressed in terms of possibility theory, whereby a candidate axiom receives a bipolar score consisting of a degree of possibility and a degree of necessity. We evaluate our proposal by applying it to the problem of testing SubClassOf axioms against the DBpedia RDF dataset

Dynamically Time-Capped Possibilistic Testing of SubClassOf Axioms Against RDF Data to Enrich Schemas

International audienceAxiom scoring is a critical task both for the automatic en-richment/learning and for the automatic validation of knowledge bases and ontologies. We designed and developed an axiom scoring heuristic based on possibility theory, which aims at overcoming some limitations of scoring heuristics based on statistical inference and taking into account the open-world assumption of the linked data on the Web. Since computing the possibilistic score can be computationally quite heavy for some candidate axioms, we propose a method based on time capping to alleviate the computation of the heuristic without giving up the precision of the scores. We evaluate our proposal by applying it to the problem of testing SubClassOf axioms against the DBpedia RDF dataset

Answering N-Relation Natural Language Questions in the Commercial Domain

International audienceThis paper presents SynchroBot, a Natural Language Question Answering system in the Commercial Domain.It relies on an RDF dataset and an RDFS ontology that we have developed for the commercial domain of the mobile phone industry. We propose an approach to understand and interpret natural language questions, based on the use of regular expressions to identify both the properties connecting entities, and their values. These regex are automatically learned from a subset of our dataset with a genetic algorithm