Fig. 7: AI utility analysis of decision adjustment with respect to RT outcome estimate for NSCLC.
From: Intricacies of human–AI interaction in dynamic decision-making for precision oncology
Scatter plots a and b, grouped by patient number, show the RT outcome estimate (RTOE) in the space spanned by tumor control probability (\({TCP}\)) and normal tissue complication probability (\({NTCP}\)) for Unassisted (\({un}\)) and AI-assisted (\({aia}\)) decision, respectively. Scatter plots c and d show the change in RTOE for adjusted decisions in \({un}\) vs \({aia\; TCP}\) space and \({un}\) vs \({aia\; NTCP}\) space, respectively, including the \(45^\circ\) Null dashed line. Out of 41 decision adjustment, 32 (76%) increased both \({TCP}\) and \({NTCP}\) while 10 (24%) decreased \({TCP}\) and \({NTCP}\). Paired plot e and violin plot f, present analysis of adjusted decision based on RTOE scoring schema \({TCP}(1-{NTCP})\) [1 for \(({tcp},{ntcp})=({{\mathrm{1,0}}})\), 0 for \({ntcp}=1\)]. Paired plots e compares the change in score for \({un}\) and \({aia}\) for each patient. Violin plot f presents the overall summary statistics for the pairwise difference in score between \({aia}\) and \({un}\): \({mean}\left({sd}\right)=0.0011(0.0058){;\; median}(Q1{|Q}3)=-0.0011(-0.0016|0.0022).\) Box plots include center line: median, box limits: upper and lower quartiles; whiskers: 1.5x interquartile range; and points: outliers.
