Fig. 6: Predictive performances with and without the incorporation of tabular data. | npj Digital Medicine

Fig. 6: Predictive performances with and without the incorporation of tabular data.

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

Fig. 6

A comparison of predictive performance when tabular data is concatenated with textual representations derived from clinical notes versus using clinical notes alone. Tabular features include demographics, laboratory results, the patient’s medical history, and physiological measurements. a Illustrates changes in Area Under the Receiver Operating Characteristic Curve (AUROC), while b illustrates changes in Area Under the Precision-Recall Curve (AUPRC). The figure shows that the relative gains achieved by incorporating tabular features are particularly pronounced for heavily imbalanced outcomes, with AUPRCs more than doubling for rare events such as Deep Vein Thrombosis (DVT) and Pulmonary Embolism (PE).

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