www.nature.com/scientificreports OPEN Area under the expiratory flow‑volume curve: predicted values by artificial neural networks Octavian C. Ioachimescu1*, James K. Stoller2 & Francisco Garcia‑Rio3 Area under expiratory flow-volume curve (AEX) has been proposed recently ...
In recent years complex networks have been identified as powerful mathematical frameworks for the adequate modeling of many applied problems in disparate research fields. Assuming a Master Equation (ME) modeling the exchange of information within the net
The ough flow rates therefore provide information about airway function Fndependently of plethysmographic measurements. The ratio of maximal expired airflow (conventionally thought to be belated to dynamic compression of airways1 to peak airflow induced by release of static compression1 at the same ...
This Bayesian network is used to calculate the probability of a patient of being alive or dead, given the gene expression of 19 genes, if the probabilistic independencies between the gene expression and the overall survival outcome as displayed on the graph hold true. Bayesian networks are very...
Data were replotted from other publications using an in-house graphical program, ‘Gtpoints’, which generates a table of data point coordinates according to the scales of axes in a *.bmp image of a given graph. Exponential regression curves (LM) were fitted in [23] for growth rate ...
A transformation was considered to make the graph linear. A natural logarithmic transformation was applied to the equations, so that the values of R2 were enhanced. A multiple regression analysis was conducted but the values of R2 did not differ from equations with a single variable and equations...
This conclusion can be reached by using the graph or by any other other reasonable criterion. The figure first appeared in [29]. It is quite clear that one could not test the orbit model on this occasion, a fact that was stressed, among other places, in a 2022 arXiv preprint of V...