Predicting pathological complete response to neoadjuvant chemoradiotherapy in rectal cancer via artificial intelligence: A systematic review and meta-analysis

Figure 1 The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram flowchart shows the number of articles (n) in the different selection stages of the selection process. AI: Artificial intelligence; pCR: Pathological complete response.

Figure 2 Hierarchical summary receiver operating characteristic curve demonstrating strong diagnostic performance with a pooled area under the curve of 0. 889 and low between-study heterogeneity (I² = 11.3%). AI: Artificial intelligence; HSROC: Hierarchical summary receiver operating characteristic; pCR: Pathological complete response; FPR: False positive rate.

Figure 3 Funnel plot showing no significant publication bias across the 13 included studies (broadly symmetric with a non-significant Egger’s test, P = 0. 65), though statistical power is limited. DOR: Diagnostic odds ratio.

Figure 4 Grading of Recommendations Assessment, Development and Evaluation- diagnostic test accuracy evidence profile rating the overall certainty of evidence as moderate. GRADE: Grading of Recommendations Assessment, Development and Evaluation; DTA: Diagnostic test accuracy; pCR: Pathological complete response.