7 results on '"Stéphanie, Combes"'
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2. Le premier data challenge organisé par la Société Française de Pathologie : une compétition internationale en 2020, un outil de recherche en intelligence artificielle pour l’avenir ?
- Author
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Agathe Delaune, Séverine Valmary-Degano, Nicolas Loménie, Karim Zryouil, Nesrine Benyahia, Olivier Trassard, Virginie Eraville, Christine Bergeron, Mojgan Devouassoux-Shisheboran, Claire Glaser, Guillaume Bataillon, Emmanuel Bacry, Stéphanie Combes, Sophie Prevot, and Philippe Bertheau
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Pathology and Forensic Medicine - Published
- 2022
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- View/download PDF
3. [The first data challenge of the french society of pathology: An international competition in 2020, a research tool in A.I. for the future?]
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Agathe, Delaune, Séverine, Valmary-Degano, Nicolas, Loménie, Karim, Zryouil, Nesrine, Benyahia, Olivier, Trassard, Virginie, Eraville, Christine, Bergeron, Mojgan, Devouassoux-Shisheboran, Claire, Glaser, Guillaume, Bataillon, Emmanuel, Bacry, Stéphanie, Combes, Sophie, Prevot, and Philippe, Bertheau
- Subjects
Pathologists ,Artificial Intelligence ,Biopsy ,Humans ,Female ,Cervix Uteri ,Algorithms - Abstract
The french society of pathology (SFP) organized in 2020 its first data challenge with the help of Health Data Hub (HDH). The organisation of this event first consisted in recruiting almost 5000 slides of uterus cervical biopsies obtained in 20 pathology centers. After having made sure that patients did not refuse to include their slides in the project, the slides were anonymised, digitized and annotated by expert pathologists, and were finally uploaded on a data challenge platform for competitors all around the world. Competitors teams had to develop algorithms that could distinguish among four diagnostic classes in epithelial lesions of uterine cervix. Among many submissions by competitors, the best algorithms obtained an overall score close to 95%. The best 3 teams shared 25k€ prizes during a special session organised during the national congress of the SFP. The final part of the competition lasted only 6 weeks and the goal of SFP and HDH is now to allow for the collection to be published in open access. This final step will allow data scientists and pathologists to further develop artificial intelligence algorithms in this medical area.
- Published
- 2021
4. The French Health Data Hub and the German Medical Informatics Initiatives Two National Projects to Promote Data Sharing in Healthcare
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Marc Cuggia, Stéphanie Combes, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire du Centre d'examens de santé de la CPAM de Côte-d'Or (Lab CES CPAM Dijon), Caisse primaire d'assurance maladie (CPAM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), and Jonchère, Laurent
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Big Data ,Information privacy ,Knowledge management ,020205 medical informatics ,data sharing ,Interoperability ,Big data ,interoperability ,02 engineering and technology ,Health informatics ,Data governance ,03 medical and health sciences ,0302 clinical medicine ,Germany ,Health care ,0202 electrical engineering, electronic engineering, information engineering ,media_common.cataloged_instance ,030212 general & internal medicine ,European union ,Survey ,ComputingMilieux_MISCELLANEOUS ,media_common ,[SDV.IB] Life Sciences [q-bio]/Bioengineering ,Section 9: Clinical Research Informatics ,Health Information Interoperability ,Information Dissemination ,business.industry ,General Medicine ,Data sharing ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,France ,business ,Delivery of Health Care ,Medical Informatics - Abstract
Objective: The diversity and volume of health data have been rapidly increasing in recent years. While such big data hold significant promise for accelerating discovery, data use entails many challenges including the need for adequate computational infrastructure and secure processes for data sharing and access. In Europe, two nationwide projects have been launched recently to support these objectives. This paper compares the French Health Data Hub initiative (HDH) to the German Medical Informatics Initiatives (MII). Method: We analysed the projects according to the following criteria: (i) Global approach and ambitions, (ii) Use cases, (iii) Governance and organization, (iv) Technical aspects and interoperability, and (v) Data privacy access/data governance. Results: The French and German projects share the same objectives but are different in terms of methodologies. The HDH project is based on a top-down approach and focuses on a shared computational infrastructure, providing tools and services to speed projects between data producers and data users. The MII project is based on a bottom-up approach and relies on four consortia including academic hospitals, universities, and private partners. Conclusion: Both projects could benefit from each other. A Franco-German cooperation, extended to other countries of the European Union with similar initiatives, should allow sharing and strengthening efforts in a strategic area where competition from other countries has increased.
- Published
- 2019
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5. Nowcasting GDP Growth by Reading Newspapers
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Stéphanie Combes, Thomas Renault, Clément Bortoli, INSEE, Centre d'économie de la Sorbonne (CES), and Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)
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Statistics and Probability ,Big Data ,Economics and Econometrics ,JEL: C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling/C.C5.C53 - Forecasting and Prediction Methods • Simulation Methods ,JEL: E - Macroeconomics and Monetary Economics/E.E3 - Prices, Business Fluctuations, and Cycles/E.E3.E32 - Business Fluctuations • Cycles ,Sociology and Political Science ,Nowcasting ,media_common.quotation_subject ,Big data ,nowcasting ,GDP ,Newspaper ,economic analysis ,Reading (process) ,0502 economics and business ,Economics ,Econometrics ,natural language analysis ,050207 economics ,Reference model ,050205 econometrics ,media_common ,JEL: E - Macroeconomics and Monetary Economics/E.E3 - Prices, Business Fluctuations, and Cycles/E.E3.E37 - Forecasting and Simulation: Models and Applications ,business.industry ,05 social sciences ,Sentiment analysis ,media ,sentiment analysis ,machine learning ,JEL Classification E32 - E37 - C53 ,1. No poverty ,16. Peace & justice ,[SHS.ECO]Humanities and Social Sciences/Economics and Finance ,Regression ,Autoregressive model ,8. Economic growth ,business - Abstract
GDP statistics in France are published on a quarterly basis, 30 days after the end of the quarter. In this article, we consider media content as an additional data source to traditional economic tools to improve short-term forecast / nowcast of French GDP. We use a database of more than a million articles published in the newspaper Le Monde between 1990 and 2017 to create a new synthetic indicator capturing media sentiment about the state of the economy. We compare an autoregressive model augmented by the media sentiment indicator with a simple autoregressive model. We also consider an autoregressive model augmented with the Insee Business Climate indicator. Adding a media indicator improves French GDP forecasts compared to these two reference models. We also test an automated approach using penalised regression, where we use the frequencies at which words or expressions appear in the articles as regressors, rather than aggregated information. Although this approach is easier to implement than the former, its results are less accurate., Bortoli Clément, Combes Stéphanie, Renault Thomas. Nowcasting GDP Growth by Reading Newspapers. In: Economie et Statistique / Economics and Statistics, n°505-506, 2018. Big Data and Statistics (Part 1) pp. 17-33.
- Published
- 2018
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6. Penser l’enseignement de l’éthique
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Stéphanie Combes
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Appropriation ,Action (philosophy) ,Reflexivity ,Ethics education ,Context (language use) ,General Medicine ,Meaning (existential) ,Sociology ,General Nursing ,Internal conflict ,Deontological ethics ,Epistemology - Abstract
Ethics emerges in the interstices of deontology, in difficult situations generating internal conflicts for the caregiver, sources of anxiety and questioning. Ethics education has always played a major in nursing programs by initiating a reflection on human values. Faced with current uncertainties in the context of care, it is now based on the appropriation of a reflexive approach to the meaning of action.
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- 2015
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7. [Thinking ethics education]
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Stéphanie, Combes
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Ethics Committees ,Ethics, Clinical ,Humans ,Clinical Competence - Abstract
Ethics emerges in the interstices of deontology, in difficult situations generating internal conflicts for the caregiver, sources of anxiety and questioning. Ethics education has always played a major in nursing programs by initiating a reflection on human values. Faced with current uncertainties in the context of care, it is now based on the appropriation of a reflexive approach to the meaning of action.
- Published
- 2015
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