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. 2020 Feb 3;10(9):5385–5391. doi: 10.1039/c9ra09475j

NanoQSAR model predictions on both the training and validation sets.

Material ID Material Training (T) validation (V) True class 1: toxic, 0: nontoxic Predicted class 1: toxic, 0: nontoxic Probability of class 0 by the reduced model Probability of class 1 by the reduced model
0 Fe2O3-PLL27 T 0 0 0.52 0.48
1 Uncoated γ-Fe2O3 (ref. 29) T 1 1 0.28 0.72
2 d-Mannose-coated-γ-Fe2O3 (ref. 29) T 1 1 0.07 0.93
3 Fe2O3-PLL29 V 1 1 0.28 0.72
4 PDMAAm-coated-γ-Fe2O3-PLL29 V 1 1 0.28 0.72
5 N-Dodecyl-PEI2k/SPIO30 T 0 0 1 0
6 Iron oxide-loaded cationic nanovesicle31 T 0 0 1 0
7 Iron oxide-loaded cationic nanovesicle31 V 0 0 1 0
8 CMCS-SPIONs32 V 0 0 1 0
9 ED-pullulan coating SPIO33 T 0 0 1 0
10 IONP-6PEG-HA34 T 0 0 1 0
11 PDMAAm-coated-γ-Fe2O3-PLL35 T 0 0 1 0
12 Citrate SPION36 V 0 0 1 0
13 d-Mannose-coated SPIONs29 T 1 1 0.15 0.85
14 SPIO@SiO2–NH2 (ref. 37) T 0 0 0.95 0.05
15 TAT-CLIO38 T 0 0 1 0