234 research outputs found
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: âMultilingual Information Extraction - ICD10 codingâ (NĂ©vĂ©ol 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 âReplication trackâ 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: âMultilingual Information Extraction - ICD10 codingâ (NĂ©vĂ©ol 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 âReplication trackâ 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 yearâs 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 yearâs new task. Word vectors and
UMLS are used as query expansion sources. Four runs were submitted to each task accordingly
A lexicon based approach to classification of ICD10 codes. IMS unipd at CLEF eHealth task 1
International audienc
Overview of the CLEF eHealth Evaluation Lab 2019
In this paper, we provide an overview of the seventh annual
edition of the CLEF eHealth evaluation lab. CLEF eHealth 2019 continues our evaluation resource building efforts around the easing and support of patients, their next-of-kins, clinical staff, and health scientists in
understanding, accessing, and authoring electronic health information in
a multilingual setting. This yearâs lab advertised three tasks: Task 1 on
indexing non-technical summaries of German animal experiments with
International Classification of Diseases, Version 10 codes; Task 2 on technology assisted reviews in empirical medicine building on 2017 and 2018
tasks in English; and Task 3 on consumer health search in mono- and
multilingual settings that builds on the 2013â18 Information Retrieval
tasks. In total nine teams took part in these tasks (six in Task 1 and three in Task 2). Herein, we describe the resources created for these tasks and
evaluation methodology adopted. We also provide a brief summary of
participants of this yearâs challenges and results obtained. As in previous years, the organizers have made data and tools associated with the
lab tasks available for future research and development
An interactive two-dimensional approach to query aspects rewriting in systematic reviews. IMS unipd at CLEF eHealth task 2
International audienc
Overview of the CLEF 2018 Consumer Health Search Task
This paper details the collection, systems and evaluation
methods used in the CLEF 2018 eHealth Evaluation Lab, Consumer Health Search (CHS) task (Task 3). This task investigates the effectiveness of search engines in providing access to medical information present on the Web for people that have no or little medical knowledge. The task aims to foster advances in the development of search technologies for Consumer Health Search by providing resources and evaluation methods to test and validate search systems. Built upon the the 2013-17 series of CLEF eHealth Information Retrieval tasks, the 2018 task considers
both mono- and multilingual retrieval, embracing the Text REtrieval Conference (TREC) -style evaluation process with a shared collection of documents and queries, the contribution of runs from participants and the subsequent formation of relevance assessments and evaluation of the participants submissions.
For this year, the CHS task uses a new Web corpus and a new set of queries compared to the previous years. The new corpus consists of Web pages acquired from the CommonCrawl and the new set of queries consists of 50 queries issued by the general public to the Health on the Net (HON) search services. We then manually translated the 50 queries to
French, German, and Czech; and obtained English query variations of the 50 original queries.
A total of 7 teams from 7 different countries participated in the 2018 CHS task: CUNI (Czech Republic), IMS Unipd (Italy), MIRACL (Tunisia), QUT (Australia), SINAI (Spain), UB-Botswana (Botswana), and UEvora (Portugal)
QUT IElab at CLEF 2018 Consumer Health Search Task: Knowledge Base Retrieval for Consumer Health Search
In this paper we describe our participation to the CLEF
2018 Consumer Health Search Task, sub task IRTask1. This track aims to evaluate and advance search technologies aimed at supporting consumers to find health advice online. Our solution addressed this challenge by extending the Entity Query Feature Expansion model (EQFE), a knowledge base (KB) query expansion method. In previous work we showed that Wikipedia, UMLS and CHV can be effective as basis for CHS
query expansions within the EQFE model. To obtain the query expansion terms, first, we mapped entity mentions to KB entities by performing exact matching. After mapping, we used the Title of the mapped KB entities as the source for expansion terms. For our first three expanded query sets, we expanded the original queries sourcing expansion terms from each of Wikipedia, the UMLS, and the CHV. For our fourth expanded query set, we combined expansion terms from Wikipedia and CHV
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