2014
DOI: 10.1007/s12247-014-9171-8
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Modeling and Optimization of Terbutaline Emitted from a Dry Powder Inhaler and Influence on Systemic Bioavailability Using Data Mining Technology

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Cited by 43 publications
(37 citation statements)
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“…Trusted models should result in validation correlation R 2 as high as those obtained during model training and testing. The root mean-squared errors (RMSE) were also calculated and compared with those of training and testing (Ali & Abdelrahim, 2014).…”
Section: Modeling and Optimization Of Ofdf Preparationmentioning
confidence: 99%
“…Trusted models should result in validation correlation R 2 as high as those obtained during model training and testing. The root mean-squared errors (RMSE) were also calculated and compared with those of training and testing (Ali & Abdelrahim, 2014).…”
Section: Modeling and Optimization Of Ofdf Preparationmentioning
confidence: 99%
“…setting integer numbers to the crosslinker type). The desired range for each of the output properties was entered into the model optimization step and the desirability function was selected as Btent^in the model optimization window [37]. The specified minimum and maximum values for the output properties were assigned as follows; %EE (68-75 %), PS (150-300 nm), ZP (9.5-15), PDI (0.1-0.3), %Rel-8 h (78-90 %), Q 24 (500-700 μg), lag time (10-20 min), and Kp (0.3-0.6).…”
Section: Modeling and Optimization Of Nanosuspension Formulationmentioning
confidence: 99%
“…In this formula, the numerator represents the sum of squares for the error term and the denominator represents the total sum of squares. 3 The values of R 2 describe how much of the variance of the dependent variable is accounted for in the model. The ANN structure I(11)-H(2)-O(1) was used for model training (linking input and the output parameters).…”
Section: Modeling Of Nanosuspension Formulaementioning
confidence: 99%