Publication RapidMiner and Tableau
UnicornHi,
We recently published a paper entitled "Normalization Methods in Time Series of Platelet Function Assays. A SQUIRE Compliant Study." in Medicine
Sven Van Poucke, MD,*, Zhongheng Zhang, MD, Mark Roest, MD, PhD, Milan Vukicevic, PhD, Maud Beran, MD, Bart Lauwereins, MD, Ming-Hua Zheng, MD, PhD, Yvonne Henskens, MD, PhD, Marcus Lancé, MD, PhD, Abraham Marcus, MD, PhD
Abstract
Background: Platelet function can be quantitatively assessed by specific assays such as light-transmission aggregometry, multiple-electrode aggregometry measuring the response to ADP, arachidonic acid, collagen, and thrombin-receptor activating peptide and viscoelastic tests such as rotational thromboelastometry (ROTEM).
Local problem: The task of extracting meaningful statistical and clinical information from high-dimensional data spaces in temporal multivariate clinical data represented in multivariate time series, is complex. Building insightful visualizations for multivariate time series demands adequate usage of normalization techniques.
Methods: In this paper various methods for data normalization (z-transformation, range transformation, proportion transformation and interquartile range) are presented and visualized discussing the most suited approach for platelet function data series.
Interventions/ Results: Normalization was calculated per assay (test) for all time points and per time point for all tests.
Conclusions: Interquartile range, range transformation and z-transformation demonstrated the correlation as calculated by the Spearman’s correlation test, when normalized per assay (test) for all time points. When normalizing per time point for all tests, no correlation could be abstracted from the charts as was the case when using all data as one dataset for normalization.
As soon as the paper is fully online, check: https://www.researchgate.net/publication/304039233_Normalization_Methods_in_Time_Series_of_Platelet_Function_Assays_A_SQUIRE_Compliant_Study
