An interactive two-dimensional approach to query aspects rewriting in systematic reviews. IMS unipd at CLEF eHealth task 2

International audienc

A lexicon based approach to classification of ICD10 codes. IMS unipd at CLEF eHealth task 1

International audienc

A reproducible approach with R markdown to automatic classification of medical certificates in French

In this paper, we report the ongoing developments of our first participation to the Cross-Language Evaluation Forum (CLEF) eHealth Task 1: “Multilingual Information Extraction - ICD10 coding” (Névéol et al., 2017). The task consists in labelling death certificates, in French with international standard codes. In particular, we wanted to accomplish the goal of the ‘Replication track’ of this Task which promotes the sharing of tools and the dissemination of solid, reproducible results.In questo articolo presentiamo gli sviluppi del lavoro iniziato con la partecipazione al Laboratorio CrossLanguage Evaluation Forum (CLEF) eHealth denominato: “Multilingual Information Extraction - ICD10 coding” (Névéol et al., 2017) che ha come obiettivo quello di classificare certificati di morte in lingua francese con dei codici standard internazionali. In particolare, abbiamo come obiettivo quello proposto dalla ‘Replication track’ di questo Task, che promuove la condivisione di strumenti e la diffusione di risultati riproducibili

A linguistic failure analysis of classification of medical publications: A study on stemming vs lemmatization

Technology-Assisted Review (TAR) systems are essential to minimize the effort of the user during the search and retrieval of relevant documents for a specific information need. In this paper, we present a failure analysis based on terminological and linguistic aspects of a TAR system for systematic medical reviews. In particular, we analyze the results of the worst performing topics in terms of recall using the dataset of the CLEF 2017 eHealth task on TAR in Empirical Medicine.I sistemi TAR (Technology-Assisted Review) sono fondamentali per ridurre al minimo lo sforzo dell’utente che intende ricercare e recuperare i documenti rilevanti per uno specifico bisogno informativo. In questo articolo, presentiamo una failure analysis basata su aspetti terminologici e linguistici di un sistema TAR per le revisioni sistematiche in campo medico. In particolare, analizziamo i topic per i quali abbiamo ottenuto dei risultati peggiori in termini di recall utilizzando il dataset di CLEF 2017 eHealth task on TAR in Empirical Medicine

Terminology in the Digital World

UIDB/03213/2020 UIDP/03213/2020This Special Issue is dedicated to the 2nd International Conference on “Multilingual digital terminology today: Design, representation formats, and management systems” (MDTT 2023), which took place in Lisbon, Portugal, from 29 to 30 June, 2023publishersversionpublishe

A Linguistic Failure Analysis of Classification of Medical Publications: A Study on Stemming vs Lemmatization

Technology-Assisted Review (TAR) systems are essential to minimize the effort of the user during the search and retrieval of relevant documents for a specific information need. In this paper, we present a failure analysis based on terminological and linguistic aspects of a TAR system for systematic medical reviews. In particular, we analyze the results of the worst performing topics in terms of recall using the dataset of the CLEF 2017 eHealth task on TAR in Empirical Medicine.I sistemi TAR (Technology-Assisted Review) sono fondamentali per ridurre al minimo lo sforzo dell’utente che intende ricercare e recuperare i documenti rilevanti per uno specifico bisogno informativo. In questo articolo, presentiamo una failure analysis basata su aspetti terminologici e linguistici di un sistema TAR per le revisioni sistematiche in campo medico. In particolare, analizziamo i topic per i quali abbiamo ottenuto dei risultati peggiori in termini di recall utilizzando il dataset di CLEF 2017 eHealth task on TAR in Empirical Medicine

Basic mechanisms of MCD in animal models.

International audienceEpilepsy-associated glioneuronal malformations (malformations of cortical development [MCD]) include focal cortical dysplasias (FCD) and highly differentiated glioneuronal tumors, most frequently gangliogliomas. The neuropathological findings are variable but suggest aberrant proliferation, migration, and differentiation of neural precursor cells as essential pathogenetic elements. Recent advances in animal models for MCDs allow new insights in the molecular pathogenesis of these epilepsy-associated lesions. Novel approaches, presented here, comprise RNA interference strategies to generate and study experimental models of subcortical band heterotopia and study functional aspects of aberrantly shaped and positioned neurons. Exciting analyses address impaired NMDA receptor expression in FCD animal models compared to human FCDs and excitatory imbalances in MCD animal models such as lissencephaly gene ablated mice as well as in utero irradiated rats. An improved understanding of relevant pathomechanisms will advance the development of targeted treatment strategies for epilepsy-associated malformations