Fig. 5: SHAP summary plots across all outcomes. | npj Digital Medicine

Fig. 5: SHAP summary plots across all outcomes.

From: The foundational capabilities of large language models in predicting postoperative risks using clinical notes

Fig. 5

SHAP values summarizing the 10 most influential tokens explaining the model’s predictions for (or against) each outcome. Each figure panel presents the most influential tokens explaining the following outcomes: a 30-day mortality, b Acute Kidney Injury (AKI), c Pulmonary Embolism (PE), d Pneumonia, e Deep Vein Thrombosis (DVT), and f Delirium. Each token typically represents a word, sub-word, or symbol. The best-performing model for each outcome was selected to perform the respective SHAP analyses. The illustration demonstrates that each token typically contributes only a small amount to any specific outcome compared to the entire set of tokens. For BioGPT-based models, < /w > marks the boundary where the word ends in the tokenizer’s vocabulary, indicating that the word is complete and no longer broken down into sub-words.

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