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In terms of model development, given that data collection was not complete for all parameters, the intent was to develop a simple model that provided relevant clinical data for a high percentage of patients and to assess the model performance as more clinical characteristics were added.
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Section "Model development" gives the insight of the models developed.
The 2D and 3D QSTR methods used for model development gave statistically significant results.
A 3D-QSAR model development gives a statistical relationship between the structures and activity of chemical compounds by calculation of 3D molecular descriptors involving steric, electrostatic and hydrophobic points marked on the 3D spatial grid.
This approach is differentiated from the usual sequential model development for given impedance spectra by its emphasis on obtaining supporting observations to guide model selection, use of error analysis to guide regression strategies and experimental design, and use of models to guide selection of new experiments.
Full details of the model development are given in this study.
Further details of model development are given in Methods.
The number of patients and events used from each study separately towards the prediction model development was given for 10 of the 15 articles, (e.g. Yap et al. [ 35]), with the remainder focusing on the numbers overall.
Through the case studies we demonstrate some steps of the model development methodology, giving special attention to the model tradeoff and conformance test.
This paper is organized as follows: "Methods" section describes the model development and gives details on the process used for evaluation.
As we demonstrated here, BSA coupled with automated model development can give superior results to the FFT when faced with short, noisy time series, non-stationarity and non-harmonic signals.
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