Vianney Jouhet
French Institute of Health and Medical Research
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Publication
Featured researches published by Vianney Jouhet.
Methods of Information in Medicine | 2013
Vianney Jouhet; Gautier Defossez; Crisap; CoRIM; Pierre Ingrand
OBJECTIVE The aim of this study was to develop and evaluate a selection algorithm of relevant records for the notification of incident cases of cancer on the basis of the individual data available in a multi-source information system. METHODS This work was conducted on data for the year 2008 in the general cancer registry of Poitou-Charentes region (France). The selection algorithm hierarchizes information according to its level of relevance for tumoral topography and tumoral morphology independently. The selected data are combined to form composite records. These records are then grouped in respect with the notification rules of the International Agency for Research on Cancer for multiple primary cancers. The evaluation, based on recall, precision and F-measure confronted cases validated manually by the registrys physicians with tumours notified with and without records selection. RESULTS The analysis involved 12,346 tumours validated among 11,971 individuals. The data used were hospital discharge data (104,474 records), pathology data (21,851 records), healthcare insurance data (7508 records) and cancer care centres data (686 records). The selection algorithm permitted performances improvement for notification of tumour topography (F-measure 0.926 with vs. 0.857 without selection) and tumour morphology (F-measure 0.805 with vs. 0.750 without selection). CONCLUSION These results show that selection of information according to its origin is efficient in reducing noise generated by imprecise coding. Further research is needed for solving the semantic problems relating to the integration of heterogeneous data and the use of non-structured information.
Journal of Biomedical Informatics | 2017
Jean Noël Nikiema; Vianney Jouhet; Fleur Mougin
In oncology, the reuse of data is confronted with the heterogeneity of terminologies. It is necessary to semantically integrate these distinct terminologies. The semantic integration by using a third terminology as a support is a conventional approach for the integration of two terminologies that are not very structured. The aim of our study was to use SNOMED CT for integrating ICD-10 and ICD-O3. We used two complementary resources, mapping tables provided by SNOMED CT and the NCI Metathesaurus, in order to find mappings between ICD-10 or ICD-O3 concepts and SNOMED CT concepts. We used the SNOMED CT structure to filter inconsistent mappings, as well as to disambiguate multiple mappings. Based on the remaining mappings, we used semantic relations from SNOMED CT to establish links between ICD-10 and ICD-O3. Overall, the coverage of ICD-O3 and ICD10 codes was over 88%. Finally, we obtained an integration of 24% (203/852) of ICD-10 concepts with 86% (888/1032) of ICD-O3 morphology concepts combined to 39% (127/330) of ICD-O3 topography concepts. Comparing our results with the 23,684 ICD-O3 pairs mapped to ICD-10 concepts in the SEER conversion file, we found 17,447 pairs of ICD-O3 concepts in common among which 11,932 pairs were integrated with the same ICD-10 concept as the SEER conversion file. The automated process leverages logical definitions of SNOMED CT concepts. While the low quality of some of these definitions impacted negatively the integration process, the identification of such situations made it possible to indirectly audit the structure of SNOMED CT.
Clinics and Research in Hepatology and Gastroenterology | 2011
Alban Michaud-Herbst; Vianney Jouhet; Pierre Ingrand; J. C. Letard; Jean-Pierre Dupuychaffray; Thierry Barrioz; Michel Beauchant
BACKGROUND AND AIMS Compliance with guidelines on colonoscopic indications can improve colorectal cancer screening efficiency. We conducted a regional practice survey of gastroenterologists working in the public and private sectors in France, and compared the results with French national guidelines. METHODS Four consecutive yearly questionnaire-based practice surveys were conducted, and remedial measures were recommended on the basis of the results. RESULTS We analyzed 5128 colonoscopies carried out by 65 practitioners. Of these, 4266 (83.2%) conformed to contemporary guidelines, 391 (7.6%) did not conform, and 471 (9.2%) could not be classified, owing to a lack of information. Remedial measures led to a significant increase in the number of colonoscopies conforming to guidelines (p=0.037) and to a significant fall in the number of unclassified procedures (p=0.0018). The distribution of colonic lesions differed between procedures that did and did not conform to guidelines (2.4% versus 0.3% of colorectal cancers, 11.4% vs. 6.9% of advanced adenomas, and 17.5% vs. 14.6% of non-advanced adenomas; p<0.0001). CONCLUSION This longitudinal multicenter survey shows that national colonoscopy guidelines are largely respected in France and improve the detection of colonic neoplasia. Practices improved following implementation of remedial measures.
Journal of Biomedical Semantics | 2017
Vianney Jouhet; Fleur Mougin; Bérénice Brechat; Frantz Thiessard
BackgroundIdentifying incident cancer cases within a population remains essential for scientific research in oncology. Data produced within electronic health records can be useful for this purpose. Due to the multiplicity of providers, heterogeneous terminologies such as ICD-10 and ICD-O-3 are used for oncology diagnosis recording purpose. To enable disease identification based on these diagnoses, there is a need for integrating disease classifications in oncology. Our aim was to build a model integrating concepts involved in two disease classifications, namely ICD-10 (diagnosis) and ICD-O-3 (topography and morphology), despite their structural heterogeneity. Based on the NCIt, a “derivative” model for linking diagnosis and topography-morphology combinations was defined and built. ICD-O-3 and ICD-10 codes were then used to instantiate classes of the “derivative” model. Links between terminologies obtained through the model were then compared to mappings provided by the Surveillance, Epidemiology, and End Results (SEER) program.ResultsThe model integrated 42% of neoplasm ICD-10 codes (excluding metastasis), 98% of ICD-O-3 morphology codes (excluding metastasis) and 68% of ICD-O-3 topography codes. For every codes instantiating at least a class in the “derivative” model, comparison with SEER mappings reveals that all mappings were actually available in the model as a link between the corresponding codes.ConclusionsWe have proposed a method to automatically build a model for integrating ICD-10 and ICD-O-3 based on the NCIt. The resulting “derivative” model is a machine understandable resource that enables an integrated view of these heterogeneous terminologies. The NCIt structure and the available relationships can help to bridge disease classifications taking into account their structural and granular heterogeneities. However, (i) inconsistencies exist within the NCIt leading to misclassifications in the “derivative” model, (ii) the “derivative” model only integrates a part of ICD-10 and ICD-O-3. The NCIt is not sufficient for integration purpose and further work based on other termino-ontological resources is needed in order to enrich the model and avoid identified inconsistencies.
medical informatics europe | 2012
Frantz Thiessard; Fleur Mougin; Gayo Diallo; Vianney Jouhet; Sébastien Cossin; Nicolas Garcelon; Boris Campillo-Gimenez; Wassim Jouini; Julien Grosjean; Philippe Massari; Nicolas Griffon; Marie Dupuch; Fayssal Tayalati; Edwige Dugas; Antonio Balvet; Natalia Grabar; Suzanne Pereira; Bruno Frandji; Stéfan Jacques Darmoni; Marc Cuggia
Family Practice | 2010
Philippe Binder; Carine Caron; Vianney Jouhet; Daniel Marcelli; Pierre Ingrand
medical informatics europe | 2015
Elise Bigeard; Vianney Jouhet; Fleur Mougin; Frantz Thiessard; Natalia Grabar
Methods | 2018
Fleur Mougin; David Auber; Romain Bourqui; Gayo Diallo; Isabelle Dutour; Vianney Jouhet; Frantz Thiessard; Rodolphe Thiébaut; Patricia Thébault
medical informatics europe | 2018
Guillaume Bouzillé; Vianney Jouhet; Bruno Turlin; Bruno Clément; Mireille Desille; Christine Riou; Moufid Hajjar; Denis Delamarre; Danielle Le Quilleuc; Frantz Thiessard; Marc Cuggia
arXiv: Computation and Language | 2018
Sébastien Cossin; Vianney Jouhet; Fleur Mougin; Gayo Diallo; Frantz Thiessard