Fig. 2: Relationship between training cases per DRG and prediction accuracy by DRG-LLaMA.

Results from DRG-LLaMA -7B with a maximum input token size of 512. a Scatter plot of top-5 prediction accuracy versus DRG ranks by number of training cases. Y-axis is top-5 prediction accuracy of each DRG label. X-axis is the rank of the 723 DRGs by their number of training cases, where DRG ranked 1^st has the most training cases, and DRG ranked 723^rd has the least training cases. Black dots indicate individual DRGs. The solid line represents smoothing spline estimated relationship (generalized cross-validation score: 0.055). The gray shaded area denotes a 95% Bayesian confidence interval for the smoothing spline estimated function. As expected, DRG-LLaMA ’s performance declined in less frequent DRGs. b Boxplot of training cases per DRG with groups of different prediction accuracy. DRGs are grouped by range of top-5 prediction accuracy as shown in X-axis. Y-axis is the number of training cases per DRG. The green line represents the median value; the box limits show the interquartile range (IQR) from the first (Q1) to third (Q3) quartiles; the whiskers extend to the furthest data point within Q1-1.5*IQR (bottom) and Q3+1.5*IQR (top). DRG groups with better prediction performance generally have a greater number of training cases, although there is a large variance in the number of training cases within the best-performing group.