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In Step 1, two different methods based on the GP distribution, namely GP-Quantile and GP-Theta, were developed for normalizing sequence count data.
The computation at a reducer based on the GP algorithm is sketched in Algorithm 4.
Then, we develop corresponding parallel solutions based on the GP and hybrid algorithms.
We develop parallel solutions to maximal clique enumeration based on the GP and hybrid algorithms and implement them on MapReduce.
In order to solve the non-convex property, the proposed algorithm is based on the GP method and a series of convex approximations are taken to achieve the global optimization in high-to-low SINR scenario, which makes our method could be applied in both high SINR and low SINR scenario.
Ascertainment based on the GP record alone was highest for prostate cancer (85.1%) and lowest for renal tract cancer (55.3%).
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An electronic screening log is generated based on the GP-approved list of patients.
Sixteen individuals who were initially identified as VZV negative by the EIA were reclassified as seropositive based on the gp-ELISA results.
For example, for the top 10% of men and women at the highest risk based on the GP-HES data (ie, those with a score of 23% or higher), QAdmissions had a sensitivity of 39% and a positive predictive value (based on the observed risk at 2 years) of 42%.
In addition to the self-reported information, data based on the GPs' EMR was analysed.
Information about the contacts was based on the GPs' direct experience as the questionnaires were filled in immediately after the contacts and recall bias was thereby minimised.
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