Comparative evaluation of multimodal large language models for Mayo Endoscopic Subscore grading in ulcerative colitis

Figure 3 Segment-wise performance evaluation of multimodal large language models in phase B. A: Overall ranking of five multimodal large language models (Gemini-2.5-Pro, Grok-4, GPT-4o, GPT-5, and Qwen-VL-Max) based on weighted composite scores; B: Summary of key performance metrics (accuracy, F1 score, κ, precision, and recall); C and D: Heatmaps illustrating segment-specific accuracy and mean absolute error across six colonic regions; E: Bar chart showing average accuracy by segment with pairwise comparisons assessed using the McNemar test (P < 0.05); F: Variability analysis of accuracy across segments (lower values indicate greater stability; G and H: Radar plots depicting segment-level and overall performance profiles across the five models. MAE: Mean absolute error; ACC: Accuracy; Corr: Correlation.