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Academic literature on the topic 'Bases de données textuelles – Soins médicaux'
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Journal articles on the topic "Bases de données textuelles – Soins médicaux"
de Lurdes Abrantes Garcia, Maria. "Projet de dictionnaire interactif multilingue de termes médicaux." Meta 42, no. 1 (September 30, 2002): 110–13. http://dx.doi.org/10.7202/003524ar.
Full textLix, L. M., R. Walker, H. Quan, R. Nesdole, J. Yang, and G. Chen. "Caractéristiques des bases de données sur les services médicaux au Canada." Maladies chroniques et blessures au Canada 32, no. 4 (September 2012): 207–15. http://dx.doi.org/10.24095/hpcdp.32.4.02f.
Full textLandry, JS, D. Croitoru, and D. Menzies. "Validation des codes de diagnostic de la CIM-9 pour la dysplasie bronchopulmonaire dans les bases de données de la Régie de l'assurance-maladie du Québec." Maladies chroniques et blessures au Canada 33, no. 1 (December 2012): 54–60. http://dx.doi.org/10.24095/hpcdp.33.1.06f.
Full textShea, AK, BR Shah, HD Clark, J. Malcolm, M. Walker, A. Karovitch, and J. Keely. "Dépistage postnatal du diabète à la suite d’un diabète sucré gestationnel : efficacité du système de rappel." Maladies chroniques au Canada 31, no. 2 (March 2011): 67–74. http://dx.doi.org/10.24095/hpcdp.31.2.02f.
Full textAllen, V. M., L. Dodds, A. Spencer, E. A. Cummings, N. MacDonald, and G. Kephart. "Pertinence d'une définition de cas administrative pour l'identification du diabète sucré préexistant à la grossesse." Maladies chroniques et blessures au Canada 32, no. 3 (June 2012): 127–35. http://dx.doi.org/10.24095/hpcdp.32.3.01f.
Full textKoehoorn, M., L. Tamburic, CB McLeod, PA Demers, L. Lynd, and SM Kennedy. "Surveillance populationnelle de l'asthme chez les travailleurs de Colombie-Britannique (Canada)." Maladies chroniques et blessures au Canada 33, no. 2 (March 2013): 101–9. http://dx.doi.org/10.24095/hpcdp.33.2.05f.
Full textTietse, Samuel. "Construction de la valeur d’usage des sources d’information stratégiques en médecine : application dans le domaine hospitalo-universitaire." Documentation et bibliothèques 50, no. 4 (April 22, 2015): 295–303. http://dx.doi.org/10.7202/1030058ar.
Full textAgweibab, Florence, and Florence Agweibab. "Why infectious diseases persist: A Rapid review of the social determinants of Malaria, Cholera, Tuberculosis and Yellow Fever in Sub-Saharan Africa." Journal of the Cameroon Academy of Sciences 19, no. 1 (May 15, 2023): 17–29. http://dx.doi.org/10.4314/jcas.v19i1.2.
Full textAraújo, Antônio Nelson Alencar de, and Marcos Alexandre Casimiro de Oliveira. "Évaluation des paramètres métaboliques de syndrome après le pontage gastrique de Roux-y." Revista Científica Multidisciplinar Núcleo do Conhecimento, November 3, 2020, 92–106. http://dx.doi.org/10.32749/nucleodoconhecimento.com.br/sante/metaboliques-de-syndrome.
Full textLeclerc, Véronique, Alexandre Tremblay, and Chani Bonventre. "Anthropologie médicale." Anthropen, 2020. http://dx.doi.org/10.17184/eac.anthropen.125.
Full textDissertations / Theses on the topic "Bases de données textuelles – Soins médicaux"
Mbaye, Ndèye Maguette. "Multimodal learning to predict breast cancer prognosis." Electronic Thesis or Diss., Université Paris sciences et lettres, 2024. http://www.theses.fr/2024UPSLM017.
Full textBreast cancer is one of the most common cancers worldwide, accounting for 12.5% of new cases each year. In 2022, around 2.3 million women were diagnosed, with over 666,000 deaths. Although electronic health records (EHRs) have revolutionized clinical research by providing valuable data, breast cancer studies rarely exploit free-text medical reports, which nonetheless contain crucial information. This thesis proposes to develop machine and deep learning models to predict breast cancer outcomes using multimodal data (French text reports, laboratory results, clinical descriptors) from a large Institut Curie cohort. Models were built to analyze these modalities separately and then jointly. Results show that the integration of textual and structured data improves the prediction of patients' survival status. Moreover, the analy-sis of predictive factors for patients' survival status opens up new perspectives for a better understanding of underlying mechanisms in breast cancer, and thus, for improving care
Najjar, Ahmed. "Forage de données de bases administratives en santé." Doctoral thesis, Université Laval, 2017. http://hdl.handle.net/20.500.11794/28162.
Full textCurrent health systems are increasingly equipped with data collection and storage systems. Therefore, a huge amount of data is stored in medical databases. Databases, designed for administrative or billing purposes, are fed with new data whenever the patient uses the healthcare system. This specificity makes these databases a rich source of information and extremely interesting. These databases can unveil the constraints of reality, capturing elements from a great variety of real medical care situations. So, they could allow the conception and modeling the medical treatment process. However, despite the obvious interest of these administrative databases, they are still underexploited by researchers. In this thesis, we propose a new approach of the mining for administrative data to detect patterns from patient care trajectories. Firstly, we have proposed an algorithm able to cluster complex objects that represent medical services. These objects are characterized by a mixture of numerical, categorical and multivalued categorical variables. We thus propose to extract one projection space for each multivalued variable and to modify the computation of the distance between the objects to consider these projections. Secondly, a two-step mixture model is proposed to cluster these objects. This model uses the Gaussian distribution for the numerical variables, multinomial for the categorical variables and the hidden Markov models (HMM) for the multivalued variables. Finally, we obtain two algorithms able to cluster complex objects characterized by a mixture of variables. Once this stage is reached, an approach for the discovery of patterns of care trajectories is set up. This approach involves the followed steps: 1. preprocessing that allows the building and generation of medical services sets. Thus, three sets of medical services are obtained: one for hospital stays, one for consultations and one for visits. 2. modeling of treatment processes as a succession of labels of medical services. These complex processes require a sophisticated method of clustering. Thus, we propose a clustering algorithm based on the HMM. 3. creating an approach of visualization and analysis of the trajectory patterns to mine the discovered models. All these steps produce the knowledge discovery process from medical administrative databases. We apply this approach to databases for elderly patients over 65 years old who live in the province of Quebec and are suffering from heart failure. The data are extracted from the three databases: the MSSS MED-ÉCHO database, the RAMQ bank and the database containing death certificate data. The obtained results clearly demonstrated the effectiveness of our approach by detecting special patterns that can help healthcare administrators to better manage health treatments.
Heurteau, Foulon Stéphanie. "Prévalence, qualité de vie et coût de la Leucémie Myéloïde Chronique en France Using healthcare claims data to analyze the prevalence of BCR-ABL-positive chronic myeloid leukemia in France: A nationwide population-based study Health state utility and quality of life measures in patients with chronic myeloid leukemia in France." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS574.
Full textChronic myeloid leukemia (CML) is a rare myeloproliferative neoplasm whose prognosis has been transformed since the 2000s by tyrosine kinase inhibitors (TKI). The dramatic increase in patients' life expectancy has led to an increase in the prevalence of CML. CML has become a chronic disease that requires daily TKI treatment for several years, but which is compatible with a normal life span for the majority of patients. TKI are expensive treatments that, taken over the long term by an increasing number of patients, increase the economic burden of the disease. TKI have side effects that affect patients' quality of life. In France, however, there is little data on the prevalence of CML, on the economic burden and quality of life.The National Health Data System (Système National des Données de Santé, SNDS) is a health care claims database that covers 98,8% of the French population and contains exhaustive data on health cares reimbursed by the Health Insurance. We built and validated an algorithm identifying patients with CML in the SNDS, based on their healthcare consumption and estimated the prevalence of the disease on December 31st, 2014. On the population identified by the algorithm, we estimated the cost of TKI in 2013 and 2014 from a health insurance perspective. We also conducted a survey in CML patients to collect their quality of life data using generic (EuroQol EQ-5D-3L), cancer-specific (EORTC-QLQ-C30) and CML-specific (EORTC-QLQ-CML-24) questionnaires. Utility values in CML patients were assessed using the French EQ-5D-3L value set.The algorithm identified 10,789 patients with CML in France in 2014, corresponding to a crude prevalence of the disease of 16.3 per 100,000 inhabitants [95% confidence interval 16.0-16.6]. In the 10,158 prevalent CML patients in 2013, the reimbursement for TKI amounted to €238 million, all insurance schemes combined. This amount increased to €247 million for the 10,789 patients prevalent in 2014. In 2014, imatinib accounted for about 55% of TKI reimbursements, followed by nilotinib (22%) and dasatinib (22%). The quality of life in CML patients was significantly impaired compared to the general population of the same sex and age, mainly in the dimensions of social functioning, role functioning and cognitive functioning. Fatigue, dyspnea and pain were the symptoms with the highest deviation from general population norms. The mean utility score (standard deviation) was 0.72 (0.25) for patients in chronic phase and 0.84 (0.21) for patients in remission without treatment.Beyond the epidemiological, clinical and economic results, this work demonstrates that using a database such as the SNDS for research is feasible, relevant but also complex in rare diseases such as CML
Renard, Laurence. "Valorisation des bases médico-administratives de l'assurance maladie pour identifier et suivre la progression d'une pathologie, en étudier la prise en charge et estimer l'impact de l'implémentation d'une politique de santé grâce à leur utilisation dans un modèle médico-économique : Application au diabète de type 2 au Luxembourg." Thesis, Paris 5, 2012. http://www.theses.fr/2012PA05S004/document.
Full textType 2 diabetes (T2D) is a chronic disease associated with many severe and costly complications. In a context of budgetary constraint, it is necessary to obtain an estimate the amount of resources to allocate to the management of chronic diseases. This includes monitoring the epidemiologic and economic evolutions. A database was built from medico-administrative databases of the national health insurance of Luxembourg. It included the healthcare consumptions associated with diabetes and its complications, of all type 2 diabetic patients treated in Luxembourg between 2000 and 2006. The objectives were to study the fields of use of this database and the possible applications for public health decision-making. This thesis gives some examples. In 2006, T2D prevalence in Luxembourg was 3.79% (N= 17070). An algorithm was built and permitted to identify three stages of diabetic nephropathy (3.77% of T2D cases in 2006). The analysis of the adherence to European follow-up guidelines showed a critical situation associated to several factors (treating physician, type of treatment, living region…). The mean costs associated with patients in dialysis were estimated at 116 647€/patient in 2006. Finally, a health-economic evaluation showed the dominance of a strategy promoting peritoneal dialysis in Luxembourg over the present situation
Books on the topic "Bases de données textuelles – Soins médicaux"
Redbooks, IBM. Mining Your Own Business in Health Care Using DB2 Intelligent Miner for Data. Ibm, 2001.
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