Explainable Machine Learning Analysis Reveals Gender Differences in the Phenotypic and Neurobiological Markers of Cannabis Use Disorder
Gregory R. Niklason, Eric Rawls, Sisi Ma, Erich Kummerfeld, Andrea M. Maxwell, Leyla R. Brucar, Gunner Drossel, Anna Zilverstand
The paper uses explainable machine learning to identify gender-specific risk factors for cannabis use disorder, finding stronger environmental influences in women and individual factors in men.
bioRxiv · Aug 30, 2021 · PreprintNeuroscience