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We report on the results of an organizational intervention designed to increase detection and intervention in cases of domestic violence among obstetric patients admitted to the hospital.
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This study was designed to increase the diagnostic detection rate for subtelomeric unbalanced chromosomal rearrangements (UCRs) that are believed to cause 3 5% of all cases of mental retardation (MR), but often remain undetected by routine karyotyping because of limited resolution in light microscopy.
Most prevention strategies to date have focussed predominantly on the second component, through education (e.g. protective behaviours) and awareness programs generally designed to increase knowledge and detection of potential abusive situations.
This is a conservative approach to CNV identification designed to increase reliability of detection.
Our ROI based approach was designed to increase sensitivity for detection of between-group differences in key cortical motor areas.
While our anomaly detection method is designed to control the FDR below a user-specified threshold, the GLRT-based method is designed to increase the probability of detection while keeping the probability of false alarm as low as possible.
A nested PCR protocol was designed to increase the sensitivity of detection of trichomonad parasite DNA in template DNA extracted from lesions sampled post mortem and to provide a diagnostic tool for cases where autolysed carcass condition precluded Trichomonas sp. culture.
The 4-nucleotide difference in the forward primer between the ERBV1 and ERBV2 assays was designed to increase the likelihood of detection of ERBV2 strains.
Homozygosity mapping was designed to increase the power of detection for recessive mutations by recognizing that a proportion of such families are inbred, and these inbred families are, in fact, informative even in the absence of affected siblings [Kruglyak et al., 1995; Lander and Botstein, 1987].
Their proposed solution is multi-dimensional, making use of four techniques designed to increase the likelihood of signal detection.
Finally the Multi Model Adaptive Linear H∞ Filter (MMALH∞F) is designed to increase the robustness of bias Detection in the presence of unknown noise statistics and unmodeled dynamics.
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