D, V. A., M, A., A, B., G, S., N, B., & D, T. (2026). Empirical Comparison of Causal Machine Learning and Post-Hoc AI Interpretability Models for Risk Factor Analysis: An Application to Medical Specialty Choice. Studies in health technology and informatics, 336, 2215. https://doi.org/10.3233/SHTI260654
Chicago Style (17th ed.) CitationD, Vicente Alvarez, Abbiati M, Bornet A, Savoldelli G, Bajwa N, and Teodoro D. "Empirical Comparison of Causal Machine Learning and Post-Hoc AI Interpretability Models for Risk Factor Analysis: An Application to Medical Specialty Choice." Studies in Health Technology and Informatics 336 (2026): 2215. https://doi.org/10.3233/SHTI260654.
MLA (9th ed.) CitationD, Vicente Alvarez, et al. "Empirical Comparison of Causal Machine Learning and Post-Hoc AI Interpretability Models for Risk Factor Analysis: An Application to Medical Specialty Choice." Studies in Health Technology and Informatics, vol. 336, 2026, p. 2215, https://doi.org/10.3233/SHTI260654.
