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Benkő E, Ilič IG, Kristó K, Regdon G Jr., Csóka I, Pintye-Hódi K, Srčič S, Sovány T. Predicting Drug Release Rate of Implantable Matrices and Better Understanding of the Underlying Mechanisms through Experimental Design and Artificial Neural Network-Based Modelling. Pharmaceutics. 2022; 14(2):228. https://doi.org/10.3390/pharmaceutics14020228

Benkő, Ernő, Ilija German Ilič, Katalin Kristó, Géza Regdon, Jr., Ildikó Csóka, Klára Pintye-Hódi, Stane Srčič, and Tamás Sovány. 2022. "Predicting Drug Release Rate of Implantable Matrices and Better Understanding of the Underlying Mechanisms through Experimental Design and Artificial Neural Network-Based Modelling" Pharmaceutics 14, no. 2: 228. https://doi.org/10.3390/pharmaceutics14020228

Benkő, E., Ilič, I. G., Kristó, K., Regdon, G., Jr., Csóka, I., Pintye-Hódi, K., Srčič, S., & Sovány, T. (2022). Predicting Drug Release Rate of Implantable Matrices and Better Understanding of the Underlying Mechanisms through Experimental Design and Artificial Neural Network-Based Modelling. Pharmaceutics, 14(2), 228. https://doi.org/10.3390/pharmaceutics14020228