Fig. 1

Flow of NLP model construction/evaluation. (a) CCA used an existing guideline modified for pharmaceutical care records, whereas PCA employed a guideline adjusted to align with patient-centered expressions. The model predicts entities corresponding to patient symptoms in the text and their factuality (either positive or negative). These predictions are then compared with the annotation results. (b) The data created under PCA was divided into training and test sets using 10-fold cross-validation, and the pre-trained BERT and LUKE models were fine-tuned. The average performance on the test data was used to evaluate model performance. (c) The applicability of the newly developed model was evaluated by comparing its predictions of actual symptoms with those of an existing model on patient-authored blogs.