APA (7th ed.) Citation

Bedolla, C. N., Gonzalez, J. M., Vega, S. J., Convertino, V. A., & Snider, E. J. (2023). An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability. Bioengineering (Basel), 10(5), 612. https://doi.org/10.3390/bioengineering10050612

Chicago Style (17th ed.) Citation

Bedolla, Carlos N., Jose M. Gonzalez, Saul J. Vega, Víctor A. Convertino, and Eric J. Snider. "An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability." Bioengineering (Basel) 10, no. 5 (2023): 612. https://doi.org/10.3390/bioengineering10050612.

MLA (9th ed.) Citation

Bedolla, Carlos N., et al. "An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability." Bioengineering (Basel), vol. 10, no. 5, 2023, p. 612, https://doi.org/10.3390/bioengineering10050612.