Titre : Organismes de services de gestion

Organismes de services de gestion : Questions médicales fréquentes

Termes MeSH sélectionnés :

Supervised Machine Learning
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gestion", "description": "Comment identifier un OSG ?\nQuels services offrent les OSG ?\nQuels sont les types d'OSG ?\nComment évaluer l'efficacité d'un OSG ?\nQuels outils utilisent les OSG ?", "url": "https://questionsmedicales.fr/mesh/D021661?mesh_terms=Supervised+Machine+Learning&page=4#section-diagnostic" }, { "@type": "MedicalWebPage", "name": "Symptômes", "headline": "Symptômes sur Organismes de services de gestion", "description": "Quels signes indiquent un besoin d'OSG ?\nComment reconnaître une mauvaise gestion ?\nQuels impacts d'une mauvaise gestion ?\nQuels symptômes d'une surcharge administrative ?\nComment détecter des erreurs fréquentes ?", "url": "https://questionsmedicales.fr/mesh/D021661?mesh_terms=Supervised+Machine+Learning&page=4#section-symptômes" }, { "@type": "MedicalWebPage", "name": "Prévention", "headline": "Prévention sur Organismes de services de gestion", "description": "Comment prévenir les erreurs de gestion ?\nQuelles pratiques recommandées pour les OSG 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} }, { "@type": "Question", "name": "Quels services offrent les OSG ?", "position": 2, "acceptedAnswer": { "@type": "Answer", "text": "Les OSG offrent des services tels que la facturation, la gestion des ressources humaines et le soutien technologique." } }, { "@type": "Question", "name": "Quels sont les types d'OSG ?", "position": 3, "acceptedAnswer": { "@type": "Answer", "text": "Les types d'OSG incluent ceux spécialisés en facturation, en gestion de la qualité et en conformité réglementaire." } }, { "@type": "Question", "name": "Comment évaluer l'efficacité d'un OSG ?", "position": 4, "acceptedAnswer": { "@type": "Answer", "text": "L'efficacité d'un OSG peut être évaluée par des indicateurs de performance tels que la satisfaction des clients et la réduction des coûts." } }, { "@type": "Question", "name": "Quels outils utilisent les OSG ?", "position": 5, "acceptedAnswer": { "@type": "Answer", "text": "Les OSG utilisent des logiciels de gestion, des systèmes de facturation et des plateformes de communication." } }, { "@type": "Question", "name": "Quels signes indiquent un besoin d'OSG ?", "position": 6, "acceptedAnswer": { "@type": "Answer", "text": "Des signes incluent une surcharge administrative, des erreurs fréquentes et une mauvaise gestion du temps." } }, { "@type": "Question", "name": "Comment reconnaître une mauvaise gestion ?", "position": 7, "acceptedAnswer": { "@type": "Answer", "text": "Une mauvaise gestion se manifeste par des retards dans les paiements, des plaintes de patients et des audits défavorables." } }, { "@type": "Question", "name": "Quels impacts d'une mauvaise gestion ?", "position": 8, "acceptedAnswer": { "@type": "Answer", "text": "Les impacts incluent une baisse de la qualité des soins, une insatisfaction des patients et des pertes financières." } }, { "@type": "Question", "name": "Quels symptômes d'une surcharge administrative ?", "position": 9, "acceptedAnswer": { "@type": "Answer", "text": "Les symptômes incluent le stress du personnel, des délais prolongés et une communication inefficace." } }, { "@type": "Question", "name": "Comment détecter des erreurs fréquentes ?", "position": 10, "acceptedAnswer": { "@type": "Answer", "text": "Des audits réguliers et des retours d'expérience des employés aident à détecter les erreurs fréquentes." } }, { "@type": "Question", "name": "Comment prévenir les erreurs de gestion ?", "position": 11, "acceptedAnswer": { "@type": "Answer", "text": "La prévention passe par des formations régulières, des audits et l'utilisation de technologies adaptées." } }, { "@type": "Question", "name": "Quelles pratiques recommandées pour les OSG ?", "position": 12, "acceptedAnswer": { "@type": "Answer", "text": "Les pratiques recommandées incluent la standardisation des processus et la mise en place de contrôles internes." } }, { "@type": "Question", "name": "Comment assurer la conformité réglementaire ?", "position": 13, "acceptedAnswer": { "@type": "Answer", "text": "Assurer la conformité nécessite des audits réguliers et une mise à jour continue des connaissances réglementaires." } }, { "@type": "Question", "name": "Quels outils pour la prévention des risques ?", "position": 14, "acceptedAnswer": { "@type": "Answer", "text": "Des outils comme les logiciels de gestion des risques et les plateformes de communication sont utiles." } }, { "@type": "Question", "name": "Comment sensibiliser le personnel aux OSG ?", "position": 15, "acceptedAnswer": { "@type": "Answer", "text": "La sensibilisation peut se faire par des formations, des réunions d'équipe et des bulletins d'information." } }, { "@type": "Question", "name": "Comment un OSG améliore-t-il la gestion ?", "position": 16, "acceptedAnswer": { "@type": "Answer", "text": "Un OSG améliore la gestion en optimisant les processus, réduisant les coûts et augmentant l'efficacité." } }, { "@type": "Question", "name": "Quels outils de gestion sont recommandés ?", "position": 17, "acceptedAnswer": { "@type": "Answer", "text": "Des outils comme les logiciels de gestion de cabinet et les systèmes de facturation sont recommandés." } }, { "@type": "Question", "name": "Comment former le personnel à l'OSG ?", "position": 18, "acceptedAnswer": { "@type": "Answer", "text": "La formation peut inclure des ateliers, des sessions de coaching et des modules en ligne sur les outils de gestion." } }, { "@type": "Question", "name": "Quels sont les bénéfices d'un OSG ?", "position": 19, "acceptedAnswer": { "@type": "Answer", "text": "Les bénéfices incluent une meilleure gestion des ressources, une réduction des coûts et une satisfaction accrue des patients." } }, { "@type": "Question", "name": "Comment évaluer un OSG ?", "position": 20, "acceptedAnswer": { "@type": "Answer", "text": "L'évaluation se fait par des indicateurs de performance, des retours d'expérience et des audits réguliers." } }, { "@type": "Question", "name": "Quelles complications d'une mauvaise gestion ?", "position": 21, "acceptedAnswer": { "@type": "Answer", "text": "Les complications incluent des pertes financières, des plaintes de patients et des sanctions réglementaires." } }, { "@type": "Question", "name": "Comment une mauvaise gestion affecte-t-elle les soins ?", "position": 22, "acceptedAnswer": { "@type": "Answer", "text": "Elle peut entraîner des retards dans les soins, une qualité inférieure et une insatisfaction des patients." } }, { "@type": "Question", "name": "Quels risques d'une surcharge administrative ?", "position": 23, "acceptedAnswer": { "@type": "Answer", "text": "Les risques incluent le burnout du personnel, des erreurs de traitement et une communication défaillante." } }, { "@type": "Question", "name": "Comment gérer les plaintes des patients ?", "position": 24, "acceptedAnswer": { "@type": "Answer", "text": "La gestion des plaintes nécessite une écoute active, une réponse rapide et des actions correctives." } }, { "@type": "Question", "name": "Quelles conséquences d'une non-conformité ?", "position": 25, "acceptedAnswer": { "@type": "Answer", "text": "Les conséquences incluent des amendes, des pertes de licence et une réputation ternie." } }, { "@type": "Question", "name": "Quels facteurs augmentent le besoin d'OSG ?", "position": 26, "acceptedAnswer": { "@type": "Answer", "text": "Les facteurs incluent la taille de la pratique, la complexité des opérations et les changements réglementaires." } }, { "@type": "Question", "name": "Comment la technologie influence-t-elle les OSG ?", "position": 27, "acceptedAnswer": { "@type": "Answer", "text": "La technologie influence les OSG en améliorant l'efficacité, la communication et la gestion des données." } }, { "@type": "Question", "name": "Quels sont les risques liés à la gestion interne ?", "position": 28, "acceptedAnswer": { "@type": "Answer", "text": "Les risques incluent le manque de formation, la résistance au changement et des processus obsolètes." } }, { "@type": "Question", "name": "Comment le marché affecte-t-il les OSG ?", "position": 29, "acceptedAnswer": { "@type": "Answer", "text": "Les fluctuations du marché peuvent influencer la demande de services et la rentabilité des OSG." } }, { "@type": "Question", "name": "Quels impacts des changements réglementaires ?", "position": 30, "acceptedAnswer": { "@type": "Answer", "text": "Les changements réglementaires peuvent nécessiter des ajustements rapides et des formations supplémentaires." } } ] } ] }

Sources (10000 au total)

Reliability of Postoperative Free Flap Monitoring with a Novel Prediction Model Based on Supervised Machine Learning.

Postoperative free flap monitoring is a critical part of reconstructive microsurgery. Postoperative clinical assessments rely heavily on specialty-trained staff. Therefore, in regions with limited spe... Postoperative data from 176 patients who received free flap surgery were prospectively collected, including free flap photographs and clinical evaluation measures. Flap circulation outcome variables i... Of 805 total included flaps, 555 (69%) were normal, 97 (12%) had arterial insufficiency, and 153 (19%) had venous insufficiency. The most effective prediction model was developed based on random fores... This study demonstrated the reliability of a machine-learning model in differentiating various types of postoperative flap circulation. This novel technique may reduce the burden of free flap monitori...

The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis.

When investigating voice disorders a series of processes are used when including voice screening and diagnosis. Both methods have limited standardized tests, which are affected by the clinician's expe... This systematic review aimed to assess the effectiveness of ML algorithms in screening and diagnosing voice disorders.... An electronic search was conducted in 5 databases. Studies that examined the performance (accuracy, sensitivity, and specificity) of any ML algorithm in detecting pathological voice samples were inclu... Of the 1409 records retrieved, 13 studies and 4079 participants were included in this review. A total of 13 ML techniques were used in the included studies, with the most common technique being least ... ML showed promising findings in the screening of voice disorders. However, the findings were not conclusive in diagnosing voice disorders owing to the limited number of studies that used ML for diagno... PROSPERO CRD42020214438; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=214438....

Inflammatory subgroups of schizophrenia and their association with brain structure: A semi-supervised machine learning examination of heterogeneity.

Immune system dysfunction is hypothesised to contribute to structural brain changes through aberrant synaptic pruning in schizophrenia. However, evidence is mixed and there is a lack of evidence of in... The total sample consisted of 1067 participants (chronic patients with schizophrenia n = 467 and healthy controls (HCs) n = 600) from the Australia Schizophrenia Research Bank (ASRB) dataset, together... An optimal clustering solution revealed five main schizophrenia groups separable from HC: Low Inflammation, Elevated CRP, Elevated IL-6/IL-8, Elevated IFN-γ, and Elevated IL-10 with an adjusted Rand i... Inflammation in schizophrenia may not be merely a case of low vs high, but rather there are pluripotent, heterogeneous mechanisms at play which could be reliably identified based on accessible, periph...

Evaluation of a Self-Supervised Machine Learning Method for Screening of Particulate Samples: A Case Study in Liquid Formulations.

Imaging is commonly used as a characterization method in the pharmaceuticals industry, including for quantifying subvisible particles in solid and liquid formulations. Extracting information beyond pa...

Harmonization of supervised machine learning practices for efficient source attribution of Listeria monocytogenes based on genomic data.

Genomic data-based machine learning tools are promising for real-time surveillance activities performing source attribution of foodborne bacteria such as Listeria monocytogenes. Given the heterogeneit... A large collection of 1 100 L. monocytogenes genomes with known sources was built according to several genomic metrics to ensure authenticity and completeness of genomic profiles. Based on these genom... The testing average accuracies from accessory genes and pan kmers were significantly higher than accuracies from core alleles or SNPs. While the accuracies from 70 and 80% of training dataset splittin... In addition to recommendations about machine learning practices for L. monocytogenes source attribution based on genomic data, the present study also provides a freely available workflow to solve othe...