In this episode Ben chats with researcher Marc Lanovaz about the exciting world of machine learning and AI as it applies to the work of behaviour analysts.


Continuing Education Units (CEUs):


Marc’s Upcoming Workshop (April 30, 2021):


Articles Referenced In This Episode:

  • Lanovaz, M. J., Giannakakos, A. R., & Destras, O. (2020). Machine learning to analyze single-case data: A proof of concept. Perspectives on Behavior Science, 43, 21-38.
  • Lanovaz, M. J. & Hranchuk, K. (2021). Machine learning to analyze single case graphs: A comparison to visual inspection. (in press).
  • Lanovaz, M. J. & Bailey, J. (2021).  Tutorial: Artificial neural networks and deep learning to analyze single case designs. (in press).
  • Bailey, J., Baker, J. C., Rzeszutek, M. J., & Lanovaz, M. J. (2021). Machine learning for supplementing behavioral assessment. Perspectives on Behavior Science. (online issue).
  • Dufour, M. M., Lanovaz, M. J., & Cardinal, P. (2020). Artificial intelligence for the measurement of stereotypy. Journal of the Experimental Analysis of Behavior, 114, 368-380.
  • Fisher, W. W., Kelley, M. E. & Lomas, J. E. (2003). Visual aids and structured criteria for improving visual inspection and interpretation of single-case designs. Journal of Applied Behavior Analysis, 36(3), 387-406.
  • Hagopian, L. P. , Fisher, W. W., Thompson, R. H., Owen-DeSchryvier, J., Iwata, B. A., & Wacker, D. P. (1997). Toward the development of structured criteria for interpretation of functional analysis data. Journal of Applied Behavior Analysis, 30(2), 313-326.
  • Turgeon, S. & Lanovaz, M. J. (2020). Tutorial: Applying machine learning in behavioral research. Perspectives on Behavior Science, 43(44), 697-723.




Open Source Framework:


Marc Lanovaz’s Lab:

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