Park, J. E., Kim, H. S., Lee, J., Cheong, E., Shin, I., Ahn, S. S., & Shim, W. H. (2020). Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation. Nature Portfolio.
Style de citation Chicago (17e éd.)Park, Ji Eun, Ho Sung Kim, Junkyu Lee, E.-Nae Cheong, Ilah Shin, Sung Soo Ahn, et Woo Hyun Shim. Deep-learned Time-signal Intensity Pattern Analysis Using an Autoencoder Captures Magnetic Resonance Perfusion Heterogeneity for Brain Tumor Differentiation. Nature Portfolio, 2020.
Style de citation MLA (8e éd.)Park, Ji Eun, et al. Deep-learned Time-signal Intensity Pattern Analysis Using an Autoencoder Captures Magnetic Resonance Perfusion Heterogeneity for Brain Tumor Differentiation. Nature Portfolio, 2020.