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Introduction Preprints have been widely cited during the COVID-19 pandemics, even in the major medical journals. However, since subsequent publication of preprint is not always mentioned in preprint repositories, some may be inappropriately cited or quoted. Our objectives were to assess the reliability of preprint citations in articles on COVID-19, to the rate of publication of preprints cited in these articles and to compare, if relevant, the content of the preprints to their published version. Methods Articles published on COVID in 2020 in the BMJ, The Lancet, the JAMA and the NEJM were manually screened to identify all articles citing at least one preprint from medRxiv. We searched PubMed, Google and Google Scholar to assess if the preprint had been published in a peer-reviewed journal, and when. Published articles were screened to assess if the title, data or conclusions were identical to the preprint version. Results Among the 205 research articles on COVID published by the four major medical journals in 2020, 60 (29.3%) cited at least one medRxiv preprint. Among the 182 preprints cited, 124 were published in a peer-reviewed journal, with 51 (41.1%) before the citing article was published online and 73 (58.9%) later. There were differences in the title, the data or the conclusion between the preprint cited and the published version for nearly half of them. MedRxiv did not mentioned the publication for 53 (42.7%) of preprints. Conclusions More than a quarter of preprints citations were inappropriate since preprints were in fact already published at the time of publication of the citing article, often with a different content. Authors and editors should check the accuracy of the citations and of the quotations of preprints before publishing manuscripts that cite them.

Background: Unstructured data from electronic health record is a gold mine. Doc’EDS is a pre-screening tool based on textual and semantic analysis. The system provides an easy-to-use interface to search documents in French. The aim of this study is to present the tools and to provide a formal evaluation of its semantic features. Material & Methods: Doc’EDS is a search tool built on the top of the clinical data warehouse developed in the Rouen University Hospital. This tool is a multilevel search engine combining structured and unstructured data. It also provides basic analytics features and semantic utilities. A formal evaluation has been conducted to measure the implemented Natural Language Processing algorithms. Results: About 17,3 million of narrative documents are contained in this CDW. The formal evaluation has been conducted over 5,000 clinical concepts that were manually collected. Negation concepts detection F-measure was 0.89, hypothesis concept detection F-measure was 0.57. Conclusion: We hereby present Doc’EDS, a semantic search tool which deals with language subtleties to enhance an advanced full text search engine dedicated to French health documents. This tool is currently used on a daily basis to help researchers identifying patients thanks to unstructured data.

Abslract-This work is concerned with ihe automatic indexing of medical images according to their medical modality for image retrieval purposes inside the ClSMeF health-catalogue. Tbe paper investigates the extraction of an accurate modality signature from gray-level medical images based on vadws histogram weigtttlng-schemes. Our medlcal image database contains six main modalities and was selected by a medical specialist, from a real healthcare environment. We extraded and compared the relative contribution of different weight+ histogram feature vectors In describing the visual content of medical images. The highest modality dassitication accuracy (78.67%) was o b~h e d with the LBP (Local Binary Pattern) weighted histogram, using a SVM classifier.

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The words of prevention, part II: ten terms in the realm of quaternary preventionAs palavras da prevenção, parte II: dez termos no âmbito da prevenção quaternária AbstractObjective: this part II article about the 'words of prevention' presents in a terminological way the content of ten current concepts used in the prevention domain which are closely linked to quaternary prevention: (1) overinformation; (2) overdiagnosis; (3) medically unexplained symptoms; (4) overmedicalization; (5) incidentaloma; (6) overscreening; (7) overtreatment; (8) shared decision making; (9) deprescribing; and (10) disease mongering. Methods: with the support of the laboratory team of the University of Rouen, France, which is dedicated to medical terminology and semantic relationships, it was possible to utilize a graphic user interface (called DBGUI) allowing the construction of links for each of chosen terms, and making automatic links to MeSH, if any. Those concepts are analyzed in their environment in current literature, as well as in their MeSH counterparts, if any, and related semantic online terminologies. Results and Discussion: the rules in terminological development aspire to cover the whole field of a concept and in the meantime, they can help to avoid the noise due to proxy and not exactly related issues. This refers to exhaustivity and specificity in information retrieval. Our finds show that referring to MeSH only in information retrieval in General Practice/Family medicine can induce much noise and poor adequacy to the subject investigated. Conclusion: gathering concepts in specially prepared terminologies for further development of ontologies is a necessity to enter in the semantic web area and the era of disseminated data in family medicine. ResumoObjetivo: este artigo parte II sobre as 'palavras da prevenção' apresenta de uma forma terminológica o conteúdo de dez conceitos atuais utilizados no domínio da prevenção, que estão intimamente ligados à prevenção quaternária: (1) sobrecarga de informação; (2) sobrediagnóstico; (3) sintomas sem explicação médica; (4) sobremedicalização; (5) incidentaloma; (6) sobrerrastreamento; (7) sobretratamento; (8) tomada de decisão compartilhada; (9) desprescrição; e (10) comercialização de doenças. Métodos: com o apoio da equipe do laboratório da Universidade de Rouen, França, que se dedica à terminologia médica e às relações semânticas, foi possível utilizar uma interface gráfica de usuário (chamado DBGUI) permitindo a construção de links para cada um dos termos escolhidos, fazendo ligações automáticas para o MeSH, caso houvesse. Estes conceitos foram analisados no seu ambiente na literatura corrente, bem como os seus homólogos no MeSH, caso houvesse, e terminologias semânticas online a eles relacionadas. Resultados e Discussão: as regras em desenvolvimento terminológico aspiram cobrir todo o campo de um conceito, ao mesmo tempo em que podem auxiliar a evitar ruídos devido a aproximações e questões não exatamente relacionadas. Isto se refere à exaustividade e especificidade na recuper...