Fig. 5: The visual differences between the supervised learning (s-model) and weakly supervised learning (w-model) models.
From: Clinically applicable optimized periprosthetic joint infection diagnosis via AI based pathology
The three-dimensional data formed by the w-model is notably distant from the coordinate point, whereas the s-model is closer to the coordinate origin. This indicates that, on average, the w-model outperforms the s-model in terms of accuracy, completeness, and reliability, thereby displaying superior visualization effects.
