Automatic case acquisition from texts for process-oriented case-based reasoning

This paper introduces a method for the automatic acquisition of a rich case representation from free text for process-oriented case-based reasoning. Case engineering is among the most complicated and costly tasks in implementing a case-based reasoning system. This is especially so for process-oriented case-based reasoning, where more expressive case representations are generally used and, in our opinion, actually required for satisfactory case adaptation. In this context, the ability to acquire cases automatically from procedural texts is a major step forward in order to reason on processes. We therefore detail a methodology that makes case acquisition from processes described as free text possible, with special attention given to assembly instruction texts. This methodology extends the techniques we used to extract actions from cooking recipes. We argue that techniques taken from natural language processing are required for this task, and that they give satisfactory results. An evaluation based on our implemented prototype extracting workflows from recipe texts is provided.Comment: Sous presse, publication pr\'evue en 201

Barriers Impacting LPNs Academic Progression

Abstract Barriers Impacting LPNs’ Academic Progression M. Dianne Nauer Chair of the Supervisory Committee: Sharon Fought, Ph.D., RN Nursing and Healthcare Leadership Licensed Practical Nurses (LPNs) desiring to academically progress in the profession of nursing face specific barriers as reported in the literature. LPNs are licensed nurses, but when trying to advance to registered nurse (RN) or earn a Bachelor of Science in Nursing (BSN), find that their experiences as nurses is not credited academically. The barriers reported by Washington State LPNs included the need to continue working, making traditional full-time class schedules a significant or extreme barrier. Cost and lack of local programs for LPN academic progression were the rated as the most significant barriers. In addition, competing with individuals with no healthcare experience for limited spaces available for academic progression by using grades from pre-requisite courses was viewed as an unfair barrier. Frustration at having to retake courses related to expiration dates, the entry requirement of expensive standardized tests, and different requirements across nursing programs were identified by LPNs as possible reasons to leave the field of nursing for other unrelated fields. The healthcare workforce is facing a potential shortage of RNs between 13.6 and 23.7 percent by 2031 (Skillman et al., 2011). This estimated shortfall makes it imperative that workforce and nursing education programs collaborate to address the barriers LPNs report as preventing their academic progression

De l'importance de la normalisation en bibliométrie

Colloque avec actes et comité de lectureSi la consultation de multiples sources d'information garantit une meilleure couverture du sujet, elle nécessite -en parallèle- de prendre en compte l'hétérogénéité des données. En effet, comme chaque producteur d'information possède son propre modèle de document, on obtient des représentations différentes d'une même information. Cette hétérogénéité occasionne deux problèmes majeurs pour la bibliométrie qui faussent statistiques et analyses. Ces difficultés concernent : • la présence de variations pour représenter une même information (auteurs, descripteurs, affiliation, etc.) ; • la présence de doublons (c'est-à-dire plusieurs représentations de la même référence bibliographique). Dans cet article, nous proposons une approche visant à pallier ces problèmes. Nous discutons tout d'abord les choix retenus en terme de normalisation et de dédoublonnage

IntoWeb : une plate forme hypertexte d'extraction de connaissances et de recherche d'information

National audienceDans cet article, nous présentons un système hypertexte, nommé IntoWeb, qui fournit aux chercheurs ou spécialistes de l'information scientifique les moyens d'exploiter les données structurées sur leur domaine et des données - textuelles - du web pour des besoins de recherche d'information, d'analyse de leur domaine ou de veille. IntoWeb est un système générique d'exploitation de données qui implémente un processus complet et itératif d'extraction de connaissances à partir de données. Le système permet de manipuler différents types d'objets (documents structurés, documents textuels, vecteurs, classifications, etc.). Des opérateurs (génération d'un vecteur à partir d'un document textuel, classification de documents structurés, etc.) permettent d'exploiter chacun des différents types d'objets à des fins d'analyses ou de recherche d'information. L'application d'un opérateur sur un ensemble d'objets produit de nouveaux objets, à leur tour exploitable dans le système. La résolution complète d'un problème d'extraction de connaissances ou de recherche d'information prend la forme d'une succession d'opérations appliquées à des objets. Le choix des objets à exploiter et des opérations à appliquer à ces objets est à la charge de l'utilisateur et dépend du problème à résoudre ; l'enchaînement des opérations est grandement facilité par IntoWeb grâce à la mise en place d'une interface web simple à utiliser

Les problèmes de variations terminologiques dans l'indexation de références bibliographiques

Colloque avec actes et comité de lectureUne activité de la terminologie est de spécifier le vocabulaire d'un domaine, en associant aux notions du domaine, les unités terminologiques les plus adéquates. On pourrait croire que le vocabulaire associé à un domaine est un ensemble limité de termes. Or, ce n'est pas le cas, car chaque acteur du domaine utilise son propre vocabulaire. C'est notamment le cas des fournisseurs d'informations -les producteurs de bases de données bibliographiques notamment- qui mettent chacun en place un système d'indexation des références propre. Les variations concernent tant par l'étendue sémantique couverte par les concepts pris en compte, que le vocabulaire associé. Nous montrons à partir d'exemples concrets que les variations terminologiques des concepts d'un domaine sont courantes dans une même langue, et qui plus est à travers différentes indexations

Acute transverse myelitis in Lyme neuroborreliosis

Introduction: Acute transverse myelitis (ATM) is a rare disorder (1-8 new cases per million of population per year), with 20% of all cases occurring in patients younger than 18years of age. Diagnosis requires clinical symptoms and evidence of inflammation within the spinal cord (cerebrospinal fluid and/or magnetic resonance imaging). ATM due to neuroborreliosis typically presents with impressive clinical manifestations. Case presentation: Here we present a case of Lyme neuroborreliosis-associated ATM with severe MRI and CSF findings, but surprisingly few clinical manifestations and late conversion of the immunoglobulin G CSF/blood index of Borrelia burgdorferi sensu lato. Conclusion: Clinical symptoms and signs of neuroborrelial ATM may be minimal, even in cases with severe involvement of the spine, as shown by imaging studies. The CSF/blood index can be negative in the early stages and does not exclude Lyme neuroborreliosis; if there is strong clinical suspicion of Lyme neuroborreliosis, appropriate treatment should be started and the CSF/blood index repeated to confirm the diagnosi

Adaptation knowledge discovery using positive and negative cases

International audienceCase-based reasoning usually exploits positive source cases, each of them consisting in a problem and a correct solution to this problem. Now, the general issue of exploiting also negative cases-i.e., problem-solution pairs where the solution answers incorrectly the problem-can be raised. Indeed, such cases are "naturally" generated by a CBR system as long as it sometimes proposes incorrect solutions. This paper aims at addressing this issue for adaptation knowledge (AK) discovery: how positive and negative cases can be used for this purpose. The idea is that positive cases are used to propose adaptation rules and that negative cases are used to filter out some of these rules. In a preliminary work, this kind of AK discovery has been applied using frequent closed itemset (FCI) extraction on variations within the case base and tested on a toy Boolean use case, with promising first results. This paper resumes this study and evaluates it on 4 benchmarks, which confirms the benefit of exploiting negative cases for AK discovery. This involves some adjustments in the data preparation and in adaptation rule filtering, in particular because FCI extraction works only with Boolean features, hence some methodology lessons learned for AK discovery with positive and negative cases

Cognitive functional MRI in temporal lobe epilepsy

Anterior temporal lobe resections (ATLR) provide an effective treatment option for patients with medically refractory temporal lobe epilepsy (TLE) rendering up to 70% of them seizure free. The goal of epilepsy surgery is to remove the brain areas generating the seizures without causing neuropsychological deficits such as language or memory dysfunction. Furthermore up to 60% of patients with TLE suffer from emotional disturbances following surgery. The principle aim of the work presented in this thesis was to improve presurgical evaluation of patients with TLE by using cognitive functional MRI (fMRI) to non-invasively localise brain areas that are essential for processing cognitive function such as language and memory function and emotional and social behaviour. 150 consecutive patients and 40 healthy controls were included in our experiments. Different fMRI paradigms for the evaluation of cognitive functions have been implemented on a 3 Tesla scanner. All subjects underwent language and memory fMRI and standard neuropsychological assessment; those patients who proceeded to have temporal lobe surgery were reinvestigated 4 months following ATLR. We studied the efficiency of reorganisation of language and memory function due to the underlying disease and in particular following ATLR. Amygdala fMRI was used to investigate potential implications on emotional and social outcome. A major part of the work included in this thesis has concentrated on the use of fMRI for the exploration and prediction of postoperative complications such as language and memory impairment but also emotional disturbances. When used in concert with other MR imaging modalities the results of these methods can be used to improve surgical strategies tailored to individual patients with regard to functional outcome, by virtue of definition of epileptic cerebral areas that need to be resected and eloquent areas that need to be spared