926 resultados para Diagnostic accuracy


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This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.

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In order to better understand the stratified combustion, the propagation of flame through stratified mixture field in laminar and turbulent flow conditions has been studied by using combined PIV/PLIF techniques. A great emphasis was placed on developing methods to improve the accuracy of local measurements of flame propagation. In particular, a new PIV approach has been developed to measure the local fresh gas velocity near preheat zone of flame front. To improve the resolution of measurement, the shape of interrogation window has been continuously modified based on the local flame topology and gas expansion effect. Statistical analysis of conditioned local measurements by the local equivalence ratio of flames allows the characterization of the properties of flame propagation subjected to the mixture stratification in laminar and turbulent flows, especially the highlight of the memory effect.

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BACKGROUND: Accurate detection of persons in need of mental healthcare is crucial to reduce the treatment gap between psychiatric burden and service use in low- and middle-income (LAMI) countries. AIMS: To evaluate the accuracy of a community-based proactive case-finding strategy (Community Informant Detection Tool, CIDT), involving pictorial vignettes, designed to initiate pathways for mental health treatment in primary care settings. METHOD: Community informants using the CIDT identified screen positive (n = 110) and negative persons (n = 85). Participants were then administered the Composite International Diagnostic Interview (CIDI). RESULTS: The CIDT has a positive predictive value of 0.64 (0.68 for adults only) and a negative predictive value of 0.93 (0.91 for adults only). CONCLUSIONS: The CIDT has promising detection properties for psychiatric caseness. Further research should investigate its potential to increase demand for, and access to, mental health services.

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OBJECTIVE: The diagnosis of Alzheimer's disease (AD) remains difficult. Lack of diagnostic certainty or possible distress related to a positive result from diagnostic testing could limit the application of new testing technologies. The objective of this paper is to quantify respondents' preferences for obtaining AD diagnostic tests and to estimate the perceived value of AD test information. METHODS: Discrete-choice experiment and contingent-valuation questions were administered to respondents in Germany and the United Kingdom. Choice data were analyzed by using random-parameters logit. A probit model characterized respondents who were not willing to take a test. RESULTS: Most respondents indicated a positive value for AD diagnostic test information. Respondents who indicated an interest in testing preferred brain imaging without the use of radioactive markers. German respondents had relatively lower money-equivalent values for test features compared with respondents in the United Kingdom. CONCLUSIONS: Respondents preferred less invasive diagnostic procedures and tests with higher accuracy and expressed a willingness to pay up to €700 to receive a less invasive test with the highest accuracy.

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Objectives: To determine whether diagnostic triage by general practitioners (GPs) or rheumatology nurses (RNs) can improve the positive predictive value of referrals to early arthritis clinics (EACs).

Methods: Four GPs and two RNs were trained in the assessment of early in?ammatory arthritis (IA) by four visits to an EAC supervised by hospital rheumatologists. Patients referred to one of three EACs were recruited for study and assessed independently by a GP, an RN and one of six rheumatologists. Each assessor was asked to record their clinical ?ndings and whether they considered the patient to have IA. Each was then asked to judge the appropriateness of the referral according to predetermined guidelines. The rheumatologists had been shown previously to have a satisfactory level of agreement in the assessment of IA.

Results: Ninety-six patients were approached and all consented to take part in the study. In 49 cases (51%), the rheumatologist judged that the patient had IA and that the referral was appropriate. The assessments of GPs and RNs were compared with those of the rheumatologists. Levels of agreement were measured using the kappa value, where 1.0 represents total unanimity. The kappa value was
0.77 for the GPs when compared with the rheumatologists and 0.79 for the RNs. Signi?cant stiffness in the morning or after rest and objective joint swelling were the most important clinical features enabling the GPs and RNs to discriminate between IA and non-IA conditions.

Conclusion: Diagnostic triage by GPs or RNs improved the positive predictive value of referrals to an EAC with a degree of accuracy approaching that of a group of experienced rheumatologists.

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Sensitive and specific urinary biomarkers can improve patient outcomes in many diseases through informing early diagnosis. Unfortunately, to date, the accuracy and translation of diagnostic urinary biomarkers into clinical practice has been disappointing. We believe this may be due to inappropriate standardization of diagnostic urinary biomarkers. Our objective was therefore to characterize the effects of standardizing urinary levels of IL-6, IL-8, and VEGF using the commonly applied standards namely urinary creatinine, osmolarity and protein. First, we report results based on the biomarker levels measured in 120 hematuric patients, 80 with pathologically confirmed bladder cancer, 27 with confounding pathologies and 13 in whom no underlying cause for their hematuria was identified, designated “no diagnosis”. Protein levels were related to final diagnostic categories (p = 0.022, ANOVA). Osmolarity (mean = 529 mOsm; median = 528 mOsm) was normally distributed, while creatinine (mean = 10163 µmol/l, median = 9350 µmol/l) and protein (0.3297, 0.1155 mg/ml) distributions were not. When we compared AUROCs for IL-6, IL-8 and VEGF levels, we found that protein standardized levels consistently resulted in the lowest AUROCs. The latter suggests that protein standardization attenuates the “true” differences in biomarker levels across controls and bladder cancer samples. Second, in 72 hematuric patients; 48 bladder cancer and 24 controls, in whom urine samples had been collected on recruitment and at follow-up (median = 11 (1 to 20 months)), we demonstrate that protein levels were approximately 24% lower at follow-up (Bland Altman plots). There was an association between differences in individual biomarkers and differences in protein levels over time, particularly in control patients.

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Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

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Evaluating the ratio of selected helium lines allows for measurement of electron densities and temperatures. This technique is applied for L-mode plasmas at TEXTOR (O. Schmitz et al., Plasma Phys. Control. Fusion 50 (2008) 115004). We report our first efforts to extend it to H-mode plasma diagnostics in DIII-D. This technique depends on the accuracy of the atomic data used in the collisional radiative model (CRM). We present predictions for the electron temperatures and densities by using recently calculated R-Matrix With Pseudostates (RMPS) and Convergent Close-Coupling (CCC) electron-impact excitation and ionization data. We include contributions from higher Rydberg states by means of the projection matrix. These effects become significant for high electron density conditions, which are typical in H-mode. We apply a non-equilibrium model for the time propagation of the ionization balance to predict line emission profiles from experimental H-mode data from DIII-D. © 2010 Elsevier B.V. All rights reserved.

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OBJECTIVE: To determine overall and disease-related accuracy of the clinical/imagiological evaluation for pulmonary infiltrates of unknown aetiology, compared with the pathological result of the surgical lung biopsy (SLB) and to evaluate the need for the latter in this setting. METHODS: We conducted a retrospective review of the experiences of SLB in 366 consecutive patients during the past 5 years. The presumptive diagnosis was based on clinical, imagiological and non-invasive or minimally invasive diagnostic procedures and compared with the gold standard of histological diagnosis by SLB. We considered five major pathological groups: diffuse parenchymal lung disease (DPLD), primitive neoplasms, metastases, infectious disease and other lesions. Patients with previous histological diagnosis were excluded. RESULTS: In 56.0% of patients (n=205) clinical evaluation reached a correct diagnosis, in 42.6% a new diagnosis was established (n=156) by the SLB, which was inconclusive in 1.4% (n=5). The pre-test probability for each disease was 85% for DPLD, 75% for infectious disease, 64% for primitive neoplasms and 60% for metastases. Overall sensitivity, specificity, positive and negative predictive values for the clinical/radiological diagnosis were 70%, 90%, 62% and 92%, respectively. For DPLD: 67%, 90%, 76% and 85%; primitive neoplasms: 47%, 90%, 46% and 90%; metastases: 99%, 79%, 60% and 99%; infectious disease 38%, 98%, 53% and 96%. CONCLUSIONS: Despite a high sensitivity and specificity of the clinical and imagiological diagnosis, the positive predictive value was low, particularly in the malignancy group. SLB should be performed in pulmonary infiltrates of unknown aetiology because the clinical/imagiological assessment missed and/or misdiagnosed an important number of patients.

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Introduction : Faute de tests diagnostiques précis, une étude histologique est souvent nécessaire pour diagnostiquer les tuméfactions latérales solides cervicales (TLSC) chez l’enfant. Nous étudierons les modalités diagnostiques pour les TLSC afin de créer une approche diagnostique standardisée intégrant de nouveaux outils diagnostics à ceux actuellement offerts. Méthodologie : Après révision des étiologies et des modalités diagnostiques, une revue de la littérature a été effectuée. Une étude rétrospective entre 2002 à 2012 est présentée suivie d’une étude de faisabilité de la cytoponction. Puis, un arbre décisionnel est créé basé sur nos résultats et sur l’avis d’un groupe d’experts de différentes disciplines médicales. Résultats : Le diagnostic différentiel des TLSC est varié, la littérature scientifique est désuète et la comparaison reste difficile. Pour nos 42 enfants avec un âge médian de sept ans, les tuméfactions inflammatoires représentent 59% (26/44 biopsies) des TLSC, surtout des lymphadénites à mycobactérie atypique (13/26) qui ont un dépistage ardu et multimodal. La biopsie fut peu contributive à la prise en charge dans 39% (17/44) des cas. La cytoponction sous échoguidance est une technique diagnostique faisable et moins invasive que la biopsie. L’arbre décisionnel offre aux cliniciens une approche diagnostique standardisée des TLSC appuyée sur des faits scientifiques que nous souhaitons valider par une étude prospective. Conclusion : Les TLSC chez l’enfant représentent un défi diagnostic et notre arbre décisionnel répond au manque de standardisation dans l’approche diagnostique. Une étude prospective sur notre arbre décisionnel est en voie d’acceptation au CHU Sainte-Justine.

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The construction sector is under growing pressure to increase productivity and improve quality, most notably in reports by Latham (1994, Constructing the Team, HMSO, London) and Egan (1998, Rethinking Construction, HMSO, London). A major problem for construction companies is the lack of project predictability. One method of increasing predictability and delivering increased customer value is through the systematic management of construction processes. However, the industry has no methodological mechanism to assess process capability and prioritise process improvements. Standardized Process Improvement for Construction Enterprises (SPICE) is a research project that is attempting to develop a stepwise process improvement framework for the construction industry, utilizing experience from the software industry, and in particular the Capability Maturity Model (CMM), which has resulted in significant productivity improvements in the software industry. This paper introduces SPICE concepts and presents the results from two case studies conducted on design and build projects. These studies have provided further in-sight into the relevance and accuracy of the framework, as well as its value for the construction sector.

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Sensitivity and specificity are measures that allow us to evaluate the performance of a diagnostic test. In practice, it is common to have situations where a proportion of selected individuals cannot have the real state of the disease verified, since the verification could be an invasive procedure, as occurs with biopsy. This happens, as a special case, in the diagnosis of prostate cancer, or in any other situation related to risks, that is, not practicable, nor ethical, or in situations with high cost. For this case, it is common to use diagnostic tests based only on the information of verified individuals. This procedure can lead to biased results or workup bias. In this paper, we introduce a Bayesian approach to estimate the sensitivity and the specificity for two diagnostic tests considering verified and unverified individuals, a result that generalizes the usual situation based on only one diagnostic test.

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When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

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Scintimammography using Tc-99m-sestamibi is a noninvasive and painless diagnostic imaging method that is used to detect breast cancer when mammography is inconclusive Because of the advantages of labeling v '7,ith Tc-99m-sestamibi and its high efficiency in detecting carcinomas, it is the most widespread agent for this purpose Its accumulation in the tumor has multifactorial causes and does not depend on the presence of architectural distortion or local or diffuse density variation in the breast The objective of tfiis study was to evaluate the accuracy of scintimammography 1 for detecting breast cancer One hundred and fifty-seven patients presenting 158 palpable and non-palpable breast nodules were evaluated Three patients were male and 154 were female, aged between 14 and 81 years All patients underwent scintimammography, and the nodule was subjected i to cytological or histological study, i e, the gold standard for diagnosing cancer One hundred and eleven malignant and 47 benign nodules were detected, with predominance of ductal carcinomas (n=94) and fibroadenoma/fibrocysiic condition (n=11/n=11), respectively The mean size was 3 11 cm (7-10 cm) among the malignant nodules and 2 07 cm among the benign nodules (0 5-10 cm) The sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 89, 89, 95, 78 and 89%, respectively Analysis on the histological types showed that the technique was more effective on tumors that were more aggressive, such as ductal carcinoma In this study, Tc-99m-sestamibi scintim immography was shown to be an important tool for diagnosing breast cancer when mammography was inconclusive

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Alterações anatômicas e fisiológicas da gravidez predispõem gestantes a infecções do trato urinário (ITU). O objetivo deste estudo foi identificar a acurácia do exame de urina simples para diagnóstico de ITU em gestantes de baixo risco. Fez-se uso do estudo de desempenho de teste diagnóstico realizado em Botucatu, SP, com 230 gestantes, entre 2006 e 2008. Os resultados mostram que a prevalência de ITU foi de 10%. A sensibilidade foi 95,6%, especificidade 63,3% e acurácia 66,5% do exame de urina simples, em relação ao diagnóstico de ITU. A análise dos valores preditivos positivo e negativo (VPP e VPN) mostrou que, na vigência de exame de urina simples normal, a chance de haver ITU foi pequena (VPN 99,2%). Frente ao resultado alterado desse exame, a probabilidade de haver ITU foi baixa (VPP 22,4%). Conclui-se que a acurácia do exame de urina simples como meio diagnóstico de ITU foi baixa, sendo indispensável a realização de urocultura para o diagnóstico.