Task 2: ShARe/CLEF eHealth evaluation lab 2014

This paper reports on Task 2 of the 2014 ShARe/CLEF eHealth evaluation lab which extended Task 1 of the 2013 ShARe/CLEF eHealth evaluation lab by focusing on template lling of disorder attributes. The task was comprised of two subtasks: attribute normalization (task 2a) and cue identication (task 2b).We instructed participants to develop a system which either kept or updated a default attribute value for each task. Participant systems were evaluated against a blind reference standard of 133 discharge summaries using Accuracy (task 2a) and F-score (task 2b). In total, ten teams participated in task 2a, and three teams in task 2b. For task 2a and 2b, the HITACHI team systems (run 2) had the highest performances, with an overall average average accuracy of 0.868 and F1-score (strict) of 0.676, respectively

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

Improving Personalized Consumer Health Search

CLEF 2018 eHealth Consumer Health Search task aims to investigate the effectiveness of the information retrieval systems in providing health information to common health consumers. Compared to previous years, this year’s task includes five subtasks and adopts new data corpus and set of queries. This paper presents the work of University of Evora participating in two subtasks: IRtask-1 and IRtask-2. It explores the use of learning to rank techniques as well as query expan- sion approaches. A number of field based features are used for training a learning to rank model and a medical concept model proposed in previous work is re-employed for this year’s new task. Word vectors and UMLS are used as query expansion sources. Four runs were submitted to each task accordingly

ShARe/CLEF eHealth evaluation lab 2014, task 3: user-centred health information retrieval

This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2014. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the effect of using additional information such as a related discharge summary and external resources such as medical ontologies on the IR effectiveness, in a monolingual and in a multilingual context. The participants were allowed to submit up to seven runs for each language, one mandatory run using no additional information or external resources, and three each using or not using discharge summaries

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

International audienc