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The number of medical websites is constantly growing [1]. Owing to the open nature of the Web, the reliability of information available on the Web is uneven. Internet users are overwhelmed by the quantity of information available on the Web. The situation is even more critical in the medical area, as the content proposed by health websites can have a direct(More)
In TREC 2014 Clinical Decision Support Track, the task was to retrieve full-texts relevant for answering generic clinical questions about medical records. For this purpose, we investigated a large range of strategies in the five runs we officially submitted. Concerning Information Retrieval (IR), we tested two different indexing levels: documents or(More)
In this paper we compare two types of corpus, focusing on the lexical mnbiguity of each of them. The first corpns consists mainly of newspaper articles and Hterature excerpts, while the second belc)ngs to the medical domain. To conduct the study, we have used two different disambiguation tools. However, first of all, we must verify the performance of each(More)
BiTeM/SIB Text Mining (http://bitem.hesge.ch/) is a University research group carrying over activities in semantic and text analytics applied to health and life sciences. This paper reports on the participation of our team at the CLEF eHealth 2016 evaluation lab. The processing applied to each evaluation corpus (QUAREO and CépiDC) was originally very(More)
The CLEF RepLab 2014 Track was the occasion to investigate the robustness of instance-based learning in a complete system for tweet monitoring and categorization based. The algorithm we implemented was a k-Nearest Neighbors. Dealing with the domain (automotive or banking) and the language (English or Spanish), the experiments showed that the categorizer was(More)
This study aims to show that health websites not asking for HONcode certification (Control sample websites A) do not respect elementary ethical standards such as the HONcode. The HONcode quality and ethical standards and the certification process have been developed by the Health on the Net Foundation to improve the transparency of the health and medical(More)
Medical institutions produce ever-increasing amount of diverse information. The digital form makes these data available for the use on more than a single patient. Images are no exception to this. However, less is known about how medical professionals search for visual medical information and how they want to use it outside of the context of a single(More)
The Internet provides a great amount of information and has become one of the communication media which is most widely used [1]. However, the problem is no longer finding information but assessing the credibility of the publishers as well as the relevance and accuracy of the documents retrieved from the web. This problem is particularly relevant in the(More)
OBJECTIVE After a review of the existing practical solution available to the citizen to retrieve eHealth document, the paper describes an original specialized search engine WRAPIN. METHOD WRAPIN uses advanced cross lingual information retrieval technologies to check information quality by synthesizing medical concepts, conclusions and references contained(More)
Biomedical professionals have access to a huge amount of literature, but when they use a search engine, they often have to deal with too many documents to efficiently find the appropriate information in a reasonable time. In this perspective, question-answering (QA) engines are designed to display answers, which were automatically extracted from the(More)