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Environnement et santé publique
Santé publique
Méthodes épidémiologiques
Statistiques comme sujet
Statistiques comme sujet : Questions médicales fréquentes
Termes MeSH sélectionnés :
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"name": "Comment les statistiques aident-elles au diagnostic médical ?",
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"name": "Quel est le lien entre statistiques et symptômes rares ?",
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"text": "Elles aident à caractériser et à comprendre la prévalence des symptômes rares."
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"name": "Comment les statistiques influencent-elles la reconnaissance des symptômes ?",
"position": 9,
"acceptedAnswer": {
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"text": "Elles fournissent des données sur les symptômes les plus courants associés à des maladies."
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"name": "Les statistiques peuvent-elles aider à l'évaluation des symptômes chroniques ?",
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"name": "Comment les statistiques contribuent-elles à la prévention des maladies ?",
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"text": "Elles identifient les facteurs de risque et évaluent l'efficacité des interventions préventives."
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"name": "Quel rôle jouent les statistiques dans les campagnes de vaccination ?",
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"name": "Les statistiques peuvent-elles aider à cibler les populations à risque ?",
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"name": "Comment les statistiques évaluent-elles les programmes de dépistage ?",
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"text": "Elles mesurent l'impact des programmes sur la détection précoce et la mortalité."
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"name": "Quel est l'impact des statistiques sur les recommandations de santé publique ?",
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"text": "Elles fournissent des données probantes pour orienter les politiques de santé publique."
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"name": "Comment les statistiques évaluent-elles l'efficacité des traitements ?",
"position": 16,
"acceptedAnswer": {
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"text": "Elles comparent les résultats cliniques entre groupes traités et non traités."
}
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"@type": "Question",
"name": "Quel rôle jouent les statistiques dans les essais cliniques ?",
"position": 17,
"acceptedAnswer": {
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"text": "Elles déterminent la taille de l'échantillon et analysent les résultats pour valider les traitements."
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"@type": "Question",
"name": "Les statistiques peuvent-elles prédire la réponse au traitement ?",
"position": 18,
"acceptedAnswer": {
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"text": "Oui, elles utilisent des modèles pour identifier les facteurs prédictifs de réponse."
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"@type": "Question",
"name": "Comment les statistiques aident-elles à personnaliser les traitements ?",
"position": 19,
"acceptedAnswer": {
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"text": "Elles analysent les données génétiques et cliniques pour adapter les traitements aux patients."
}
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"@type": "Question",
"name": "Quel est l'impact des statistiques sur le suivi des traitements ?",
"position": 20,
"acceptedAnswer": {
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"text": "Elles permettent d'évaluer l'adhérence et les effets secondaires des traitements au fil du temps."
}
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"@type": "Question",
"name": "Comment les statistiques aident-elles à identifier les complications ?",
"position": 21,
"acceptedAnswer": {
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"text": "Elles analysent la fréquence des complications dans les études cliniques et épidémiologiques."
}
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"name": "Quel rôle jouent les statistiques dans la gestion des complications ?",
"position": 22,
"acceptedAnswer": {
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"text": "Elles évaluent les résultats des traitements pour minimiser les complications post-opératoires."
}
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"@type": "Question",
"name": "Les statistiques peuvent-elles prédire les complications ?",
"position": 23,
"acceptedAnswer": {
"@type": "Answer",
"text": "Oui, elles utilisent des modèles pour identifier les facteurs de risque de complications."
}
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"@type": "Question",
"name": "Comment les statistiques influencent-elles la recherche sur les complications ?",
"position": 24,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elles fournissent des données pour orienter les recherches sur la prévention des complications."
}
},
{
"@type": "Question",
"name": "Quel est l'impact des statistiques sur le suivi des complications ?",
"position": 25,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elles permettent d'évaluer l'évolution des complications et d'ajuster les traitements."
}
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"@type": "Question",
"name": "Comment les statistiques identifient-elles les facteurs de risque ?",
"position": 26,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elles analysent les données épidémiologiques pour établir des associations entre facteurs et maladies."
}
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"@type": "Question",
"name": "Quel rôle jouent les statistiques dans l'évaluation des facteurs de risque ?",
"position": 27,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elles quantifient l'impact des facteurs de risque sur l'incidence des maladies."
}
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"@type": "Question",
"name": "Les statistiques peuvent-elles aider à réduire les facteurs de risque ?",
"position": 28,
"acceptedAnswer": {
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"text": "Oui, elles évaluent l'efficacité des interventions pour réduire les comportements à risque."
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"name": "Comment les statistiques influencent-elles les recommandations sur les facteurs de risque ?",
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"name": "Quel est l'impact des statistiques sur la sensibilisation aux facteurs de risque ?",
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This study aimed to explore the risk factors for failed treatment of carbapenem-resistant...
A total of 189 CRAB-VAP patients were included in the safety analysis set from two Grade 3 A national-level hospitals between 1 January 2022 and 31 December 2022. The risk factors for failed treatment...
Of the 189 patients, 106 (56.1%) patients were in the successful treatment group, and 83 (43.9%) patients were in the failed treatment group. The multivariate logistic model analysis showed that age (...
Age, hypoproteinemia, daily dose, medication within 14 days prior to surgical intervention, and microbial clearance are all significant risk factors for failed treatment with CRAB-VAP, with the nomogr...
Early diagnosis and prompt treatment of malaria in young children are crucial for preventing the serious stages of the disease. If delayed treatment-seeking habits are observed in certain areas, targe...
This study applied multivariate binary logistic regression model diagnostics and geospatial logistic model to identify traditional authorities in Malawi where caregivers have unusual health-seeking be...
Both models showed significant variability in treatment-seeking habits of caregivers between villages. The mixed-effects logit model residual identified Vuso Jere, Kampingo Sibande, Ngabu, and Dzoole ...
These findings suggest that using a combination of multivariate regression model residuals and geospatial statistics can help in identifying communities with distinct treatment-seeking patterns for ch...
Coronavirus has long been considered a global epidemic. It caused the deaths of nearly 7.01 million individuals and caused an economic downturn. The number of verified coronavirus cases is increasing ...
To explore the potential value of ultrasound radiomics in differentiating between benign and malignant breast nodules by extracting the radiomic features of two-dimensional (2D) grayscale ultrasound i...
The clinical and ultrasound data of 1000 female patients (500 pathologically benign patients, 500 pathologically malignant patients) who underwent breast ultrasound examinations at our hospital were r...
Eight ultrasound radiomic features were selected to establish the model. The AUC values of the model were 0.979 and 0.977 in the training and validation sets, respectively (P = .0029), indicating good...
The proposed logistic regression model based on 2D grayscale ultrasound images could facilitate differential diagnosis of benign and malignant breast nodules. The model, which was constructed using ul...
At present, the number of enterprises in financial crisis in China is rising sharply, and the ability of enterprises to resist risks is generally weak. Therefore, it is necessary to establish a corpor...
The structure and diversity of microbial communities are intrinsically hierarchical due to the shared evolutionary history of their constituents. This history is typically captured through taxonomic a...
Green logistics (GL) is the main development trend of modern logistics. The analysis of green logistics topics and their evolution is helpful in grasping its development trend and doing research facin...
When developing a clinical prediction model, assuming a linear relationship between the continuous predictors and outcome is not recommended. Incorrect specification of the functional form of continuo...
We searched PubMed for clinical prediction model studies developing a logistic regression model for a binary outcome, published between July 01, 2020, and July 30, 2020....
In total, 118 studies were included in the review (18 studies (15%) assessed the linearity assumption or used methods to handle nonlinearity, and 100 studies (85%) did not). Transformation and splines...
Though widely recommended not to categorize continuous predictors or assume a linear relationship between outcome and continuous predictors, most studies categorize continuous predictors, few studies ...
Road traffic injuries cost countries 3% of their annual GDP. In developing countries like India, every year around 150,000 people die on roads. The type of vehicles involved in a crash contribute majo...
To explore if random forest (RF) model can predict the prognosis of hospital-acquired Klebsiella pneumoniae infection as well as traditional logistic regression(LR) model....
A total of 254 cases of hospital-acquired Klebsiella pneumoniae infection in a tertiary hospital in Beijing from January 2016 to December 2020 were retrospectively collected. Appropriate influencing f...
The prediction accuracy of the LR model was 87.0%, the true positive rate of the LR model was 94.7%; the false negative rate of the LR model was 5.3%; the false positive rate of the LR model was 35%; ...
The RF model has higher specificity, sensitivity, and accuracy for the prognostic prediction of hospital-acquired Klebsiella pneumoniae infection than the LR model and has greater clinical application...