Figure 1.

Data engineering, model design, training, and selection processes; the design allows the ML model to predict the diagnostic status (ASD vs. TD) of the child from narrative production and expressive vocabulary. DT: decision trees, GB: gradient boosting; HGB: hist gradient boosting; and XGB: XGBoost.