Query expansion using medical information extraction for improving information retrieval in French medical domain

Many users’ queries contain references to named entities, and this is particularly true in the medical field. Doctors express their information needs using medical entities as they are elements rich with information that helps to better target the relevant documents. At the same time, many resources have been recognized as a large container of medical entities and relationships between them such as clinical reports; which are medical texts written by doctors. In this paper, we present a query expansion method that uses medical entities and their semantic relations in the query context based on an external resource in OWL. The goal of this method is to evaluate the effectiveness of an information retrieval system to support doctors in accessing easily relevant information. Experiments on a collection of real clinical reports show that our approach reveals interesting improvements in precision, recall and MAP in medical information retrieval

Removal of Tannic Acid From Aqueous Solution by Cloud Point Extraction and Investigation of Surfactant Regeneration by Microemulsion Extraction

The aim of this work is the extraction of tannic acid (TA) with two commercial nonionic surfactants, separately: Lutensol ON 30 and Triton X-114 (TX-114).The experimental cloud point extraction results are expressed by four responses to surfactant concentration and temperature variations: extent of TA extraction (E), remaining solute (X s,w) and surfactant (X t,w) concentrations in dilute phase and volume fraction of coacervate (Φc) at equilibrium. An empirical smoothing method was used and the results are represented on three dimensional plots. In optimal conditions, the extraction extent of TA reaches 95 and 87 % using TX-114 and Lutensol ON 30, respectively. Sodium sulfate, cetyltrimethylammonium bromide (CTAB) addition and pH effect are also studied. Finally, the possibility of recycling of the surfactant is proved

Rponse au dficit hydrique progressif chez la lentille: vers une diffrentiation morpho-physiologique entre des accessions sauvages (Lens orientalis), populations locales et lignes avances (Lens culinaris Medik.)

La Lentille (Lens culinaris Medik.) contribue la scurit alimentaire et la durabilit des systmes agricoles. La tolrance la scheresse est un objectif majeur pour la cration varitale. Cette tude visait la comparaison des rponses des populations locales, accessions sauvages Lens orientalis et des lignes avances au stress hydrique progressif en pots sous serre. Les accessions sauvages ont dmontr une grande tolrance au stress hydrique par rapport aux lignes avances et populations locales. Elles avaient un ratio des racines/la matire sche arienne, contenu relatif en eau des feuilles, une dpression de la temprature du couvert et une stabilit de la membrane cellulaire plus levs ainsi qu’une svrit de fltrissement et un taux de perte d’eau des feuilles plus faible. Une diffrentiation gntique claire pour la tolrance la scheresse entre les trois groupes gntiques a t montre. Diffrentes rponses morpho-physiologiques du matriel gntique ont t observes, correspondant diffrents mcanismes de tolrance la scheresse. Les accessions sauvages, les lignes avances et les nouvelles varits amliores INRA Maroc A3, A4, A5, A6 et A7 ainsi que la lentille de Zaer, une population locale bnficiant d’un label de qualit connue dans le pays, ont t identifies comme les plus tolrantes la scheresse parmi le matriel gntique tudi. Ces accessions pourraient tre utilises dans les programmes d’amlioration gntique dans la perspective de dvelopper des varits tolrantes la scheresse. Lentil (Lens culinaris, Medik.) is one of the world’s most important food legumes, contributing to food security and sustainable farming. Drought tolerance is a major objective of breeding programs. This work aimed at comparing genotypes with different genetic background (landraces, Lens orientalis wild accessions and elite advanced lines) under two watering regimes (well-watered; progressive water deficit). Drought tolerance was assessed based on morphological and physiological parameters: leaves’ relative water content and water losing rate, cell membrane stability, canopy temperature, root/shoot ratio, seedling vigor, wilting severity and harvest index. The evaluation was carried out in a greenhouse pot experiment using three replications. Wild accessions were more drought tolerant than advanced lines and landraces. They had higher root/shoot ratio, leaves’ relative water content, canopy temperature depression and cell membrane stability and lower wilting severity and leaves’ water losing rate. Discriminant factor analysis highlighted a clear genetic differentiation for drought tolerance between the three genetic groups. Different morpho-physiological responses of the studied genetic material have been observed corresponding to different drought tolerance mechanisms. Wild accessions, advanced lines and new improved INRA Morocco varieties A3, A4, A5, A6 and A7 as well as lentil of Zaer, a specific landrace with specific quality mark distinction known in the country, were identified as the most drought tolerant among the studied material. These accessions could be used in genetic improvement programs for developing drought tolerant varietiesThe accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Using local grammar for entity extraction from clinical reports

Information Extraction (IE) is a natural language processing (NLP) task whose aim is to analyze texts written in natural language to extract structured and useful information such as named entities and semantic relations linking these entities. Information extraction is an important task for many applications such as bio-medical literature mining, customer care, community websites, and personal information management. The increasing information available in patient clinical reports is difficult to access. As it is often in an unstructured text form, doctors need tools to enable them access to this information and the ability to search it. Hence, a system for extracting this information in a structured form can benefits healthcare professionals. The work presented in this paper uses a local grammar approach to extract medical named entities from French patient clinical reports. Experimental results show that the proposed approach achieved an F-Measure of 90. 06%