Using Natural Language Processing to Develop an Automated Orthodontic Diagnostic System
Table 2: Automatic evaluation of treatment ranking models by Spearman’s rho.
['[EMPTY]', '[ITALIC] ρ']
As each method has Spearman’s rank correlation coefficient exceeding 0.4, it can be interpreted that these estimation results have a positive correlation with human evaluation. Compared to the BoW model, the OoK model is expected to be able to obtain feature vectors that reflect an annotator’s expertise, so it is considered that high performance has been achieved. Furthermore, the USE model achieves the highest performance because the dense vectors obtained by deep learning can represent rich information.