Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models

Table 2 Performance metrics for different data models

	Cutoff	AUC	Accuracy	Precision	Sensitivity	Specificity	F1 Score
Logistic Regression
Structured Data	0.744	0.704	0.635	0.847	0.623	0.668	0.718
Unstructured Data	0.783	0.760	0.696	0.882	0.685	0.730	0.771
Combined (Structured + Unstructured)	0.779	0.784	0.717	0.894	0.705	0.753	0.788
Mean (Structured + Unstructured)	0.735	0.787	0.732	0.888	0.733	0.728	0.803
Random Forest
Structured Data	0.726	0.701	0.652	0.845	0.654	0.647	0.737
Unstructured Data	0.715	0.749	0.696	0.868	0.698	0.687	0.774
Combined (Structured + Unstructured)	0.720	0.766	0.712	0.875	0.716	0.698	0.787
Mean (Structured + Unstructured)	0.718	0.779	0.723	0.882	0.726	0.716	0.797
Gradient boosting
Structured Data	0.737	0.711	0.651	0.845	0.652	0.649	0.736
Unstructured Data	0.747	0.763	0.714	0.876	0.719	0.700	0.790
Combined (Structured + Unstructured)	0.759	0.789	0.726	0.892	0.719	0.745	0.797
Mean (Structured + Unstructured)	0.740	0.789	0.729	0.889	0.727	0.734	0.800
Extreme Gradient Boosting
Structured Data	0.803	0.678	0.623	0.836	0.615	0.645	0.709
Unstructured Data	0.897	0.734	0.682	0.866	0.679	0.691	0.761
Combined (Structured + Unstructured)	0.893	0.779	0.714	0.886	0.708	0.733	0.787
Mean (Structured + Unstructured)	0.782	0.759	0.699	0.870	0.702	0.691	0.777

ISSN: 1472-6947