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Image Search Results
Journal: PLoS ONE
Article Title: Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation
doi: 10.1371/journal.pone.0191921
Figure Lengend Snippet: Five fold-cross validation of ANN model showed good agreement between experimental vs predicted trough/dose ratio (r 2 = 0.94 to 0.96).
Article Snippet: As shown in , the five-fold cross-validation of
Techniques: Biomarker Discovery
Journal: PLoS ONE
Article Title: Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation
doi: 10.1371/journal.pone.0191921
Figure Lengend Snippet: ANN simulation illustrating (A) Age-dependent changes in bioavailability of tacrolimus in men and women; (B) Bioavailability of tacrolimus in men and women according to BMI.
Article Snippet: As shown in , the five-fold cross-validation of
Techniques:
Journal: PLoS ONE
Article Title: Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation
doi: 10.1371/journal.pone.0191921
Figure Lengend Snippet: ANN simulations depicting genotype based association of tacrolimus bioavailability in (A) men; (B) women.
Article Snippet: As shown in , the five-fold cross-validation of
Techniques:
Journal: PLoS ONE
Article Title: Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation
doi: 10.1371/journal.pone.0191921
Figure Lengend Snippet: ANN simulations depicting gene-gene interactions in modulating tacrolimus bioavailability. (A) CYP3A5*3 -ABCB1 1236 C>T; (B) CYP3A5-ABCB1 2677 G>T/A; (C) CYP3A5-ABCB1 3435 C>T.
Article Snippet: As shown in , the five-fold cross-validation of
Techniques: