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Some Methods to Maximize Extraction of Scientific Knowledge from Parallel Group Randomized Trials
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作者 Anders M.Galloe Carsten T.Larsen 《World Journal of Cardiovascular Diseases》 2015年第1期19-26,共8页
The amount of scientific knowledge from randomized parallel group trials have been improved by the CONSORT Guideline, but important intelligence with important clinical implications remains to be extracted. This may t... The amount of scientific knowledge from randomized parallel group trials have been improved by the CONSORT Guideline, but important intelligence with important clinical implications remains to be extracted. This may though be obtained if the conventional statistical significance testing is supplied by 1) Addition of an unbiased and reproducible quantification of the magnitude or size of the clinical significance/importance of a difference in treatment outcome;2) Addition of a quantification of the credulity of statements on any possible effect size and finally;3) Addition of a quantification of the risk of committing an error when the null hypothesis is either accepted or rejected. These matters are crucial to proper conversion of trial results into good usage in every-day clinical practice and may produce immediate therapeutic consequence in quite opposite direction to the usual ones. In our drug eluting stent trial “SORT OUT II”, the implementation of our suggestions would have led to immediate cessation of use of the paclitaxel-eluting stent, which the usual Consort like reporting did not lead to. Consequently harm to subsequent patients treated by this stent might have been avoided. Our suggestions are also useful in cancer treatment trials and in fact generally so in most randomized trial. Therefore increased scientific knowledge with immediate and potentially altered clinical consequence may be the result if hypothesis testing is made complete and the corresponding adjustments are added to the CONSORT Guideline—first of all— for the potential benefit of future patients. 展开更多
关键词 parallel Group randomized Trials
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Efficient Parallel Algorithms for Some Graph Theory Problems
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作者 马军 马绍汉 《Journal of Computer Science & Technology》 SCIE EI CSCD 1993年第4期362-366,共5页
In this paper,a sequential algorithm computing the all vertex pair distance matrix D and the path matrix Pis given.On a PRAM EREW model with p,1≤p≤n^2,processors,a parallel version of the sequential algorithm is sho... In this paper,a sequential algorithm computing the all vertex pair distance matrix D and the path matrix Pis given.On a PRAM EREW model with p,1≤p≤n^2,processors,a parallel version of the sequential algorithm is shown.This method can also be used to get a parallel algorithm to compute transitive closure arrayof an undirected graph.The time complexify of the parallel algorithm is O(n^3/p).If D,P andare known,it is shown that the problems to find all connected components, to compute the diameter of an undirected graph,to determine the center of a directed graph and to search for a directed cycle with the minimum(maximum)length in a directed graph can all be solved in O(n^2/p^+ logp)time. 展开更多
关键词 parallel graph algorithms shortest paths transitive closure connected components diameter of graph center of graph directed cycle with the minimum (maximum)length parallel random access machines (PRAMs)
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