Search

Your search keyword '"Thirion B"' showing total 353 results
Start Over Author "Thirion B"
353 results on '"Thirion B"'

1. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.

Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2024

2. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, R. A., Markiewicz, C. J., Appelhoff, S., Ashar, Y. K., Auer, T., Baillet, S., Bansal, S., Beltrachini, L., Bertazzoli, G., Bhogawar, S., Blair, R. W., Bortoletto, M., Boudreau, M., Brooks, T. L., Bénar, C. G., Calhoun, V. D., Castelli, F. M., Clement, P., Cohen, A. L., Cohen-Adad, J., Dambrosio, S., Delorme, A., Devinsky, O., Draschkow, D., Duff, E. P., Dupre, E., Earl, E., Esteban, O., Feingold, F. W., Flandin, G., Galassi, A., Gallitto, G., Ganz, M., Gholam, J., Ghosh, S. S., Giacomel, A., Gillman, A. G., Gleeson, P., Gramfort, A., Guay, S., Guidali, G., Halchenko, Y. O., Handwerker, D. A., Hardcastle, N., Herholz, P., Hermes, D., Honey, C. J., Innis, R. B., Ioanas, H.-I., Jahn, A., Karakuzu, A., Keator, D. B., Kiar, G., Kincses, B., Laird, A. R., Lau, J. C., Lazari, A., Legarreta, J. H., Li, A., Li, X., Love, B. C., Lu, H., Maumet, C., Mazzamuto, G., Meisler, S. L., Mikkelsen, M., Mutsaerts, H., Nichols, T. E., Nikolaidis, A., Nilsonne, G., Niso, G., Norgaard, M., Okell, T. W., Oostenveld, R., Ort, E., Park, P. J., Pawlik, M., Pernet, C. R., Pestilli, F., (0000-0002-3201-6002) Petr, J., Phillips, C., Poline, J.-B., Pollonini, L., Raamana, P. R., Ritter, P., Rizzo, G., Robbins, K. A., Rockhill, A. P., Rogers, C., Rokem, A., Rorden, C., Routier, A., Saborit-Torres, J. M., Salo, T., Schirner, M., Smith, R. E., Spisak, T., Sprenger, J., Swann, N. C., Szinte, M., Takerkart, S., Thirion, B., Thomas, A. G., Torabian, S., Varoquaux, G., Vaya, M. D. L. I., Voytek, B., Welzel, J., Wilson, M., Hollander, G., Vega, A., Gorgolewski, K. J., Poldrack, R. A., Markiewicz, C. J., Appelhoff, S., Ashar, Y. K., Auer, T., Baillet, S., Bansal, S., Beltrachini, L., Bertazzoli, G., Bhogawar, S., Blair, R. W., Bortoletto, M., Boudreau, M., Brooks, T. L., Bénar, C. G., Calhoun, V. D., Castelli, F. M., Clement, P., Cohen, A. L., Cohen-Adad, J., Dambrosio, S., Delorme, A., Devinsky, O., Draschkow, D., Duff, E. P., Dupre, E., Earl, E., Esteban, O., Feingold, F. W., Flandin, G., Galassi, A., Gallitto, G., Ganz, M., Gholam, J., Ghosh, S. S., Giacomel, A., Gillman, A. G., Gleeson, P., Gramfort, A., Guay, S., Guidali, G., Halchenko, Y. O., Handwerker, D. A., Hardcastle, N., Herholz, P., Hermes, D., Honey, C. J., Innis, R. B., Ioanas, H.-I., Jahn, A., Karakuzu, A., Keator, D. B., Kiar, G., Kincses, B., Laird, A. R., Lau, J. C., Lazari, A., Legarreta, J. H., Li, A., Li, X., Love, B. C., Lu, H., Maumet, C., Mazzamuto, G., Meisler, S. L., Mikkelsen, M., Mutsaerts, H., Nichols, T. E., Nikolaidis, A., Nilsonne, G., Niso, G., Norgaard, M., Okell, T. W., Oostenveld, R., Ort, E., Park, P. J., Pawlik, M., Pernet, C. R., Pestilli, F., (0000-0002-3201-6002) Petr, J., Phillips, C., Poline, J.-B., Pollonini, L., Raamana, P. R., Ritter, P., Rizzo, G., Robbins, K. A., Rockhill, A. P., Rogers, C., Rokem, A., Rorden, C., Routier, A., Saborit-Torres, J. M., Salo, T., Schirner, M., Smith, R. E., Spisak, T., Sprenger, J., Swann, N. C., Szinte, M., Takerkart, S., Thirion, B., Thomas, A. G., Torabian, S., Varoquaux, G., Vaya, M. D. L. I., Voytek, B., Welzel, J., Wilson, M., Hollander, G., Vega, A., and Gorgolewski, K. J.

Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, and the mechanisms by which it has been extended. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2024

3. Local Optimal Transport for Functional Brain Template Estimation

Author

Bazeille, T., Richard, H., Janati, H., Thirion, B., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Chung, Albert C. S., editor, Gee, James C., editor, Yushkevich, Paul A., editor, and Bao, Siqi, editor

Published
2019
Full Text
View/download PDF

4. Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates

Author

Janati, H., Bazeille, T., Thirion, B., Cuturi, M., Gramfort, A., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Chung, Albert C. S., editor, Gee, James C., editor, Yushkevich, Paul A., editor, and Bao, Siqi, editor

Published
2019
Full Text
View/download PDF

6. A group model for stable multi-subject ICA on fMRI datasets

Author

Varoquaux, G., Sadaghiani, S., Pinel, P., Kleinschmidt, A., Poline, J. B., and Thirion, B.

Subjects
Statistics - Applications, Statistics - Methodology
Abstract

Spatial Independent Component Analysis (ICA) is an increasingly used data-driven method to analyze functional Magnetic Resonance Imaging (fMRI) data. To date, it has been used to extract sets of mutually correlated brain regions without prior information on the time course of these regions. Some of these sets of regions, interpreted as functional networks, have recently been used to provide markers of brain diseases and open the road to paradigm-free population comparisons. Such group studies raise the question of modeling subject variability within ICA: how can the patterns representative of a group be modeled and estimated via ICA for reliable inter-group comparisons? In this paper, we propose a hierarchical model for patterns in multi-subject fMRI datasets, akin to mixed-effect group models used in linear-model-based analysis. We introduce an estimation procedure, CanICA (Canonical ICA), based on i) probabilistic dimension reduction of the individual data, ii) canonical correlation analysis to identify a data subspace common to the group iii) ICA-based pattern extraction. In addition, we introduce a procedure based on cross-validation to quantify the stability of ICA patterns at the level of the group. We compare our method with state-of-the-art multi-subject fMRI ICA methods and show that the features extracted using our procedure are more reproducible at the group level on two datasets of 12 healthy controls: a resting-state and a functional localizer study.

Published
2010
Full Text
View/download PDF

12. Interoperable atlases of the human brain

Author

Amunts, K., Hawrylycz, M. J., Van Essen, D. C., Van Horn, J. D., Harel, N., Poline, - B.J., De Martino, F., Bjaalie, J. G., Dehaene-Lambertz, G., Dehaene, S., Valdes-Sosa, P., Thirion, B., Zilles, K., Hill, S. L., Abrams, M. B., Tass, P. A., Vanduffel, W., Evans, A. C., and Eickhoff, S. B.

Published
2014
Full Text
View/download PDF

23. Improving accuracy and power with transfer learning using a meta-analytic database

Author

Schwartz, Y., Gael Varoquaux, Pallier, C., Pinel, P., Poline, J. B., Thirion, B., Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Service NEUROSPIN (NEUROSPIN), Neuroimagerie cognitive - Psychologie cognitive expérimentale (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Saclay (COmUE)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, and Schwartz, Yannick

Subjects
FOS: Computer and information sciences, Meta-analysis, machine learning, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, fMRI, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Machine Learning (stat.ML), [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], multiple comparison
Abstract

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies the specification of regions of interest (ROIs) that are usually selected on the basis of the coordinates of previously detected effects. In this paper, we propose to use a database of images, rather than coordinates, and frame the problem as transfer learning: learning a discriminant model on a reference task to apply it to a different but related new task. To facilitate statistical analysis of small cohorts, we use a sparse discriminant model that selects predictive voxels on the reference task and thus provides a principled procedure to define ROIs. The benefits of our approach are twofold. First it uses the reference database for prediction, i.e. to provide potential biomarkers in a clinical setting. Second it increases statistical power on the new task. We demonstrate on a set of 18 pairs of functional MRI experimental conditions that our approach gives good prediction. In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts., MICCAI, Nice : France (2012)

Published
2012

25. A method of cross-lingual consumer health information retrieval

Author

Névéol, A., Pereira, S., Lina F Soualmia, Thirion, B., Darmoni, S. J., Chercheur indépendant, Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU), CHU Rouen, Laboratoire d'Informatique Médicale et de BIOinformatique (LIM&BIO), Université Paris 13 (UP13), Lecroq, Thierry, and Soualmia, Lina F

Subjects
MEDLINE, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Information Storage and Retrieval, Multilingualism, [INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR], France, Medical Informatics, ComputingMilieux_MISCELLANEOUS
Abstract

International audience; OBJECTIVES: This paper presents a method of cross-language information retrieval aiming to make medical information available to patients in French and English, regardless of the query language they wish to use. METHODS: We describe the two MeSH-related terminologies used in this work. We show that the French patient synonyms included in CISMeF can be automatically mapped to the English consumer-oriented health topics used in MEDLINEplus, via the MeSH thesaurus. The links between French and English patient terms thus inferred can subsequently be exploited to automatically translate patient queries. RESULTS: 129 MEDLINEplus topics have been mapped to 142 CISMeF patient synonyms. Contextual links for cross-language retrieval have been added to the patient dedicated French information Gateway CISMeF. Conclusion: we have presented an efficient method for cross-lingual patient information retrieval in French and English, which may also be applied to other language pairs, subject to the availability of patient terminologies and of the MeSH thesaurus in these languages.

Published
2006

26. Doc'CISMEF: a search tool based on 'encapsulated' MeSH thesaurus

Author

Stefan Darmoni, Thirion B, Jp, Leroy, Douyère M, Lacoste B, Godard C, Rigolle I, Brisou M, Videau S, Goupy E, Piot J, Quéré M, Ouazir S, and Abdulrab H

Subjects
Internet, Subject Headings, National Library of Medicine (U.S.), Vocabulary, Controlled, Abstracting and Indexing, Computers, Information Storage and Retrieval, Software, United States
Abstract

In the year 2000, the Internet became a major source of health information for the health professional and the Netizen. The objective of Doc'CISMeF (D'C) was to create a powerful generic search tool based on an structured information model which â encapsulates' the MeSH thesaurus to index and retrieve quality health resources on the Internet. To index resources, D'C uses four sections in its information model: 'meta-term', keyword, subheading, and resource type. Two search options are available: simple and advanced. The simple search requires the end-user to input a single term or expression. If this term belongs to the D'C information structure model, it will be exploded. If not, a full-text search is performed. In the advanced search, complex searches are possible combining Boolean operators with meta-terms, keywords, subheadings and resource types. D'C uses two standard tools for organising information: the MeSH thesaurus and the Dublin Core metadata format. Resources included in D'C are described according to the following elements: title, author or creator, subject and keywords, description, publisher, date, resource type, format, identifier, and language.

Published
2001

27. A study comparing centralized CD-ROM and decentralized intranet access to MEDLINE

Author

Stefan Darmoni, Benichou J, Thirion B, Mf, Hellot, and Fuss J

Subjects
Computer Communication Networks, User-Computer Interface, CD-ROM, MEDLINE, Physicians, Surveys and Questionnaires, InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, France, Articles, humanities
Abstract

The purpose of this study was to evaluate the efficacy of a decentralized intranet access in each medical department as opposed to centralized unique MEDLINE access in the medical library.A two-phase questionnaire to evaluate MEDLINE use was given to junior and senior physicians at Rouen University Hospital (RUH). Phase I (August-October 1996) corresponded to a time period when centralized access was the only means of access available and phase II (August-October 1997) to a time period following the introduction of decentralized intranet access.A total of 168 physicians filled out at least one phase of the questionnaire, among whom 123 (73%) filled out both phases. Use of MEDLINE significantly increased in 1997 (average of 10.2+/-1.1 searches in three months) versus 1996 (average of 4.9+/-0.7 searches in three months, P0.0001). The aim of searches changed, becoming significantly more care oriented in phase II (P0.0001). The number of searches performed by the physicians alone increased (P0.0001) and searches performed by the librarian decreased (P0.0001) in phase II. The method of searches also changed, as searches by author (P0.0001), by journal (P = 0.0042), and by free word (P = 0.0027) increased in phase II. Knowledge of the following concepts of MEDLINE significantly increased: explosion (P0.0001), scope note (P0.0001), Abridged Index Medicus (AIM) journals (P0.0001), Medical Subject Headings (MeSH) qualifier (P0.0001), and focus (P0.0001).A decentralized intranet access to MEDLINE increased the number of searches and knowledge of this bibliographic database. MEDLINE intranet access modified the purpose and the methods of searching.

Published
2000

28. CISMeF: cataloque and index of French speaking health resources

Author

Stefan Darmoni, Jp, Leroy, Baudic F, Douyère M, Piot J, and Thirion B

Subjects
Canada, Internet, Vocabulary, Controlled, Abstracting and Indexing, MEDLINE, Catalogs as Topic, Health Resources, Humans, France, Switzerland
Abstract

In 1999, the Internet has become a major source of health information. The objective of CISMeF is to catalogue and index the main French-speaking sites and documents concerning health. Currently, the number of resources already totalled over 6,100 with a mean of 75 new sites each week. CISMeF contains a thematic index, including medical specialities and an alphabetic index. CISMeF uses two standard tools for organising information: the MeSH (Medical Subject Heading) thesaurus from the Medline bibliographic database (National Library of Medicine) and the Dublin Core metadata format. A brief description of the site is systematically added. CISMeF respects the Net Scoring, criteria to assess the quality of health information on the Internet. The CISMeF project fulfils a valuable tool for the French-speaking health community: 2,500 machines visit the Web site each working day.

Published
2000

29. [CISMeF: catalog and index of French-speaking medical sites]

Author

Stefan Darmoni, Jp, Leroy, Baudic F, Douyère M, Piot J, and Thirion B

Subjects
Internet, Subject Headings, National Library of Medicine (U.S.), Abstracting and Indexing, MEDLINE, Programming Languages, France, Cataloging, Ireland, Software, United States
Abstract

The Internet has now become a major source of health information. The aim of CISMeF is to catalogue and index the main French-speaking sites and documents concerning health. This project was initiated by Rouen University Hospital. Its URL is http://www.chu-rouen.fr/cismef. CISMeF covers all areas of health care and medical sciences, and is indexed both alphabetically and according to subject. It was set up on a Sun workstation under the Sun UNIX operating system and is entirely based on static HTML. By May 1999, the number of sites and documents indexed was already over 6,500, with a mean of 75 new sites added each week. CISMeF is updated via a five-step process: resource collection, filtering, description, classification, and indexing. The Net Scoring criteria are used to assess the quality of health information on the Internet. These criteria concern eight categories: credibility, content, links, design, interactivity, quantitative aspects, ethics and accessibility. CISMeF uses two standard tools to organize information: the MeSH (medical subject heading) thesaurus from the Medline reference database (National Library of Medicine, USA) and the Dublin core metadata format. The sites and documents included in CISMeF are described using the following elements from the Dublin core project: title, author or creator, subject and keywords, description, publisher, date, resource type, format, identifier, and language.

Published
1999

30. Understanding MeSH for literature searches

Author

Fremer, Edgar, Darmoni, S.J., Thirion, B., Lowe, Henry J., and Barnett, Octo

Subjects
United States. National Library of Medicine, MEDLINE (Database) -- Usage, Subject headings -- Usage, Information services -- Study and teaching, Database searching -- Methods
Published
1995

Catalog

Books, media, physical & digital resources
See catalog results