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Start Over Topic drug research and development Language english Publisher hal ccsd
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1. Vigi4Med Scraper: A Framework for Web Forum Structured Data Extraction and Semantic Representation

Author

Audeh, Bissan, Beigbeder, Michel, Zimmermann, Antoine, Jaillon, Philippe, Bousquet, Cédric, Choo, Kim-Kwang Raymond, Département Informatique et systèmes intelligents ( FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne, Laboratoire Hubert Curien [Saint Etienne] (LHC), Institut d'Optique Graduate School (IOGS)-Université Jean Monnet [Saint-Étienne] (UJM)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherches en Cancérologie de Toulouse (CRCT), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of Glasgow, Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE), Laboratoire Hubert Curien (LHC), Institut d'Optique Graduate School (IOGS)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), and Université Paris 13 (UP13)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, Download, Physiology, Social Sciences, lcsh:Medicine, 02 engineering and technology, Representation (arts), Infographics, Scraper site, Sociology, 0202 electrical engineering, electronic engineering, information engineering, Medicine and Health Sciences, Biomechanics, Computer Networks, lcsh:Science, Multidisciplinary, Data Collection, Applied Mathematics, Simulation and Modeling, computer.file_format, Semantics, Data model, Social Networks, Physical Sciences, 020201 artificial intelligence & image processing, Graphs, Algorithms, Network Analysis, Research Article, Computer and Information Sciences, Drug Research and Development, Research and Analysis Methods, Drug Safety, 020204 information systems, Humans, Social media, RDF, Structure (mathematical logic), Pharmacology, Internet, Information retrieval, Biological Locomotion, Data Visualization, lcsh:R, Biology and Life Sciences, Linguistics, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Crawling, lcsh:Q, computer, Social Media, Mathematics
Abstract

View at Publisher| Export | Download | Add to List| More... PLoS ONE Volume 12, Issue 1, January 2017, Article number e0169658 Open Access Vigi4Med scraper: A framework for web forum structured data extraction and semantic representation (Article) Audeh, B.a , Beigbeder, M.a, Zimmermann, A.a, Jaillon, P.b, Bousquet, C.c a University of Lyon, MINES Saint-Etienne, CNRS, Hubert Curien Laboratory, UMR 5516, Saint-Etienne, France b Ecole Nationale Superieure des Mines de Saint-Etienne, Saint-Etienne, France c INSERM, U1142, LIMICS, Paris, France View additional affiliations View references (36) Abstract The extraction of information from social media is an essential yet complicated step for data analysis in multiple domains. In this paper, we present Vigi4Med Scraper, a generic open source framework for extracting structured data from web forums. Our framework is highly configurable; using a configuration file, the user can freely choose the data to extract from any web forum. The extracted data are anonymized and represented in a semantic structure using Resource Description Framework (RDF) graphs. This representation enables efficient manipulation by data analysis algorithms and allows the collected data to be directly linked to any existing semantic resource. To avoid server overload, an integrated proxy with caching functionality imposes a minimal delay between sequential requests. Vigi4Med Scraper represents the first step of Vigi4Med, a project to detect adverse drug reactions (ADRs) from social networks founded by the French drug safety agency Agence Nationale de Securite du Medicament (ANSM). Vigi4Med Scraper has successfully extracted greater than 200 gigabytes of data from the web forums of over 20 different websites. © 2017 Audeh et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Published
2017

2. Finding Alternatives to the Dogma of Power Based Sample Size Calculation: Is a Fixed Sample Size Prospective Meta-Experiment a Potential Alternative?

Author

Elsa Tavernier, Bruno Giraudeau, Ludovic Trinquart, Centre Hospitalier Régional Universitaire de Tours (CHRU de Tours), MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes (UN)-Université de Nantes (UN), Centre d'Epidémiologie Clinique, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Hôtel Dieu, Université Paris Descartes - Faculté de Médecine (UPD5 Médecine), Université Paris Descartes - Paris 5 (UPD5), Equipe 5 : METHODS - Méthodes de l’évaluation thérapeutique des maladies chroniques (CRESS - U1153), Université Paris Descartes - Paris 5 (UPD5)-Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA), Centre d’Investigation Clinique [Tours] CIC 1415 (CIC ), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Hôpital Bretonneau-Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Francois Rabelais [Tours], PRES Centre-Val de Loire Université, Centre Hospitalier Régional Universitaire de Tours (CHRU TOURS), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Hôpital Bretonneau-Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Bruere, Gérard, Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, Economics, [SDV]Life Sciences [q-bio], Statistics as Topic, Normal Distribution, Social Sciences, lcsh:Medicine, 030204 cardiovascular system & hematology, law.invention, 0302 clinical medicine, Mathematical and Statistical Techniques, Randomized controlled trial, law, Models, Statistics, Medicine and Health Sciences, 030212 general & internal medicine, lcsh:Science, Multidisciplinary, Research Assessment, Statistical, 3. Good health, [SDV] Life Sciences [q-bio], Research Design, Meta-analysis, Physical Sciences, Probability distribution, Statistics (Mathematics), Algorithms, Type I and type II errors, Research Article, Drug Research and Development, Systematic Reviews, Clinical Research Design, Research and Analysis Methods, External validity, Normal distribution, 03 medical and health sciences, Replication (statistics), Confidence Intervals, Humans, Clinical Trials, Computer Simulation, Statistical Methods, Pharmacology, Models, Statistical, lcsh:R, Probability Theory, Probability Distribution, Confidence interval, Sample size determination, Sample Size, lcsh:Q, Clinical Medicine, Mathematics, Finance, Meta-Analysis
Abstract

International audience; Sample sizes for randomized controlled trials are typically based on power calculations. They require us to specify values for parameters such as the treatment effect, which is often difficult because we lack sufficient prior information. The objective of this paper is to provide an alternative design which circumvents the need for sample size calculation. In a simulation study, we compared a meta-experiment approach to the classical approach to assess treatment efficacy. The meta-experiment approach involves use of meta-analyzed results from 3 randomized trials of fixed sample size, 100 subjects. The classical approach involves a single randomized trial with the sample size calculated on the basis of an a priori-formulated hypothesis. For the sample size calculation in the classical approach, we used observed articles to characterize errors made on the formulated hypothesis. A prospective meta-analysis of data from trials of fixed sample size provided the same precision, power and type I error rate, on average, as the classical approach. The meta-experiment approach may provide an alternative design which does not require a sample size calculation and addresses the essential need for study replication; results may have greater external validity.

Published
2016