58,061 research outputs found
Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis.
BACKGROUND: Automated digital microscopy has the potential to improve the diagnosis of tuberculosis (TB), particularly in settings where molecular testing is too expensive to perform routinely. The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain. METHODS: Using data from a demonstration study of an automated digital microscopy system (TBDx, Applied Visual Systems, Inc.), we performed an economic evaluation of TB diagnosis in South Africa from the health system perspective. The primary outcome was the incremental cost per new TB diagnosis made. We considered costs and effectiveness of different algorithms for automated digital microscopy, including as a stand-alone test and with confirmation of positive results with Xpert MTB/RIF ('Xpert', Cepheid, Inc.). Results were compared against both manual microscopy and universal Xpert testing. RESULTS: In settings willing to pay 1280 per incremental TB diagnosis (95% uncertainty range, UR: 3440) in the base case, but improved under conditions likely reflective of many settings in sub-Saharan Africa: 450-956 per diagnosis (95% UR: 2910) when the prevalence of multidrug-resistant TB was lowered to 1%. CONCLUSIONS: Although universal Xpert testing is the preferred algorithm for TB diagnosis when resources are sufficient, automated digital microscopy can identify the majority of cases and halve the cost of diagnosis and treatment when resources are more scarce and multidrug-resistant TB is not common
Theoretical Interpretations and Applications of Radial Basis Function Networks
Medical applications usually used Radial Basis Function Networks just as Artificial Neural Networks. However, RBFNs are Knowledge-Based Networks that can be interpreted in several way: Artificial Neural Networks, Regularization Networks, Support Vector Machines, Wavelet Networks, Fuzzy Controllers, Kernel Estimators, Instanced-Based Learners. A survey of their interpretations and of their corresponding learning algorithms is provided as well as a brief survey on dynamic learning algorithms. RBFNs' interpretations can suggest applications that are particularly interesting in medical domains
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Evaluation of critical congenital heart defects screening using pulse oximetry in the neonatal intensive care unit.
ObjectiveTo evaluate the implementation of early screening for critical congenital heart defects (CCHDs) in the neonatal intensive care unit (NICU) and potential exclusion of sub-populations from universal screening.Study designProspective evaluation of CCHD screening at multiple time intervals was conducted in 21 NICUs across five states (n=4556 infants).ResultsOf the 4120 infants with complete screens, 92% did not have prenatal CHD diagnosis or echocardiography before screening, 72% were not receiving oxygen at 24 to 48 h and 56% were born ⩾2500 g. Thirty-seven infants failed screening (0.9%); none with an unsuspected CCHD. False positive rates were low for infants not receiving oxygen (0.5%) and those screened after weaning (0.6%), yet higher among infants born at <28 weeks (3.8%). Unnecessary echocardiograms were minimal (0.2%).ConclusionGiven the majority of NICU infants were ⩾2500 g, not on oxygen and not preidentified for CCHD, systematic screening at 24 to 48 h may be of benefit for early detection of CCHD with minimal burden
Development of diagnostic and prognostic algorithms for SF6 puffer circuit breakers from transient waveforms: a validation proposal
- This paper presents a validation proposal for development of diagnostic and prognostic algorithms for SF6 puffer circuit-breakers reproduced from actual site waveforms. The re-ignition/restriking rates are duplicated in given circuits and the cumulative energy dissipated in interrupters by the restriking currents. The targeted objective is to provide a simulated database for diagnosis of re-ignition/restrikes relating to the phase to earth voltage and the number of re-ignition/restrikes as well as estimating the remaining life of SF6 circuit-breakers. The model-based diagnosis of a tool will be useful in monitoring re-ignition/restrikes as well as predicting a nozzle’s lifetime. This will help ATP users with practical study cases and component data compilation for shunt reactor switching and capacitor switching. This method can be easily applied with different data for the different dielectric curves of circuit breakers and networks. This paper presents modelling details and some of the available cases, required project support, the validation proposal, the specific plan for implementation and the propsed main contributions
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