questionsmedicales.fr
Personnes
Visiteurs des patients
Visiteurs des patients : Questions médicales fréquentes
Termes MeSH sélectionnés :
Diagnostic
2
Évaluation
Bien-être
Visiteurs
Solitude
Anxiété
Dépression
Symptômes
2
Isolement social
Anxiété
Dépression
Douleur
Soutien émotionnel
Visiteurs
Prévention
2
Isolement
Visites
Technologie
Hygiène
Protocoles
Visiteurs
Traitements
2
Traitement
Soutien social
Visiteurs
Gestion des visites
Sécurité
Hôpital
Complications
2
Complications
Santé mentale
Santé physique
Stress
Visiteurs
Planification
Facteurs de risque
2
Âge avancé
Maladies chroniques
Isolement social
Soins intensifs
Soutien
Visiteurs
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"description": "Comment évaluer l'impact des visites sur le patient ?\nQuels signes indiquent qu'un patient a besoin de visites ?",
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"position": 6,
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Expert en Médecine, Optimisation des Parcours de Soins et Révision Médicale
Validation scientifique effectuée le 26/03/2025
Contenu vérifié selon les dernières recommandations médicales
3 publications dans cette catégorie
Affiliations :
Animal Welfare Science Centre, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, North Melbourne, VIC, Australia.
Publications dans "Visiteurs des patients" :
3 publications dans cette catégorie
Affiliations :
Animal Welfare Science Centre, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, North Melbourne, VIC, Australia.
Publications dans "Visiteurs des patients" :
3 publications dans cette catégorie
Affiliations :
Department of Wildlife Conservation and Science, Zoos Victoria, Parkville, VIC, Australia.
Publications dans "Visiteurs des patients" :
3 publications dans cette catégorie
Affiliations :
Animal Welfare Science Centre, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, North Melbourne, VIC, Australia.
Publications dans "Visiteurs des patients" :
2 publications dans cette catégorie
Affiliations :
Hartpury University and Hartpury College, Gloucester, United Kingdom.
Publications dans "Visiteurs des patients" :
2 publications dans cette catégorie
Affiliations :
Emergency Department, ShanXi Provincial People's Hospital, Taiyuan, ShanXi, China.
School of Nursing, Midwifery & Health Systems, University College Dublin, Dublin, Ireland.
Publications dans "Visiteurs des patients" :
2 publications dans cette catégorie
Affiliations :
School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland.
Publications dans "Visiteurs des patients" :
2 publications dans cette catégorie
Affiliations :
School of Nursing, Midwifery & Health Systems, University College Dublin, Dublin, Ireland.
Publications dans "Visiteurs des patients" :
2 publications dans cette catégorie
Affiliations :
Department of Pathology and Laboratory Medicine, BC Children's Hospital, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada. Electronic address: jocelyn.srigley@cw.bc.ca.
Publications dans "Visiteurs des patients" :
2 publications dans cette catégorie
Affiliations :
Western Michigan University, Kalamazoo, USA.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Department of Animal Ecology and Tropical Biology, University of Würzburg, Würzburg, Germany.
Department of Agricultural Resource Management, University of Embu, Embu, Kenya.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Department of Entomology and Plant Pathology, University of Arkansas at Fayetteville, Fayetteville, AR, USA.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Department of Animal Ecology and Tropical Biology, University of Würzburg, Würzburg, Germany.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Division of Hematology, Oncology and Palliative Care, Massey Cancer Center, Virginia Commonwealth University, Richmond, Va; Department of Pediatrics, Baylor College of Medicine, Houston, Tex. Electronic address: audra.iness@bcm.edu.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Department of Bioengineering, College of Engineering, Virginia Commonwealth University, Richmond, Va.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
Division of Epidemiology, Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Va.
Publications dans "Visiteurs des patients" :
1 publication dans cette catégorie
Affiliations :
School of Medicine, California Northstate University, Elk Grove, Calif.
Publications dans "Visiteurs des patients" :
This study aimed to investigate the relationship between cardiomegaly and aortic arch calcification (AAC) and overall/cardiovascular mortality in hemodialysis patients....
We conducted a retrospective cohort study and enrolled patients who underwent initial hemodialysis. Cardiomegaly and AAC were determined by chest radiography and classified into four groups according ...
In multivariate Cox regression analysis, those in CTR ≤ 0.5 and HGAAC [hazard ratio (95% confidence interval): 2.07 (1.14-3.77)], CTR > 0.5 & LGAAC [3.60 (2.07-6.25)] and CTR > 0.5 & HGAAC [3.42 (2.03...
Combined cardiomegaly and AAC predicted overall and cardiovascular mortality in hemodialysis patients....
The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box ...
Building a reliable and precise model for disease classification and identifying abnormal sites can provide physicians assistance in their decision-making process. Deep learning based image analysis i...
We aimed to characterize novel coronavirus infections based on imaging [chest X-ray and chest computed tomography (CT)] at the time of admission....
We extracted data from 396 patients with laboratory-confirmed COVID-19 who were managed at 68 hospitals in Japan from January 25 to September 2, 2020. Case patients were categorized as severe (death o...
The median age of the 396 patients was 48 years (interquartile range 28-65) and 211 (53.3%) patients were male. Thirty-two severe cases were compared to 364 non-severe cases. At the time of admission,...
Chest CT and X-ray scores and the identification of cardiomegaly could be useful for classifying severe COVID-19 on admission....
Cardiac disease is one of the leading causes of death in dogs. Automatic cardiomegaly detection has great significance in helping clinicians improve the accuracy of the diagnosis process. Deep learnin...
Hypereosinophilic syndrome is a heterogeneous group of disorders, the majority of which are idiopathic. Cardiac manifestations, particularly eosinophilic myocarditis and endomyocardial fibrosis, are a...
Cardiovascular diseases are among the major health problems that are likely to benefit from promising developments in quantum machine learning for medical imaging. The chest X-ray (CXR), a widely used...
In recent years, several deep learning approaches have been successfully applied in the field of medical image analysis. More specifically, different deep neural network architectures have been propos...
Cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR (>0.55) is often an indicator of an underlying pathological condition. The accurate ...
We propose a deep learning (DL)-based model for automatic CTR calculation to assist radiologists with rapid diagnosis of cardiomegaly and thus optimise the radiology flow....
The study population included 1012 posteroanterior CXRs from a single institution. The Attention U-Net DL architecture was used for the automatic calculation of CTR. An observer performance test was c...
U-Net model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], specificity >99%, precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. Furthermore, the sensitivity of th...
Our segmentation-based AI model demonstrated high specificity (>99%) and sensitivity (80%) for CTR calculation. The performance of the radiologist on the observer performance test improved significant...
Semantic segmentation for diagnosing chest-related diseases like cardiomegaly, emphysema, pleural effusions, and pneumothorax is a critical yet understudied tool for identifying the chest anatomy. A d...