Table 2.

The performance of fusion model using Random Forest

Model	Training cohort						Testing cohort
	AUC (95% CI)	Accuracy	Sensitivity	Specificity	Precision	F1-Score	AUC (95% CI)	Accuracy	Sensitivity	Specificity	Precision	F1-Score
Clinical	0.592(0.504–0.681)	0.603	0.682	0.492	0.652	0.667	0.707(0.549–0.865)	0.676	0.696	0.643	0.762	0.728
Radiologic	0.568(0.527–0.61)	0.500	0.153	0.984	0.929	0.263	0.573(0.462–0.684)	0.486	0.217	0.929	0.833	0.344
Habitat	0.817(0.748–0.886)	0.747	0.741	0.754	0.808	0.773	0.700(0.523–0.878)	0.703	0.783	0.571	0.750	0.766
CRH	0.837(0.774–0.899)	0.767	0.812	0.705	0.793	0.802	0.766(0.61–0.921)	0.757	0.783	0.714	0.818	0.800
AP + T2WI	0.845(0.782–0.908)	0.747	0.671	0.852	0.864	0.755	0.798(0.646–0.950)	0.784	0.870	0.643	0.800	0.834
H1 − AP+T2WI	0.817(0.748–0.885)	0.747	0.659	0.869	0.875	0.752	0.834(0.684–0.984)	0.838	0.913	0.714	0.840	0.875
AP + VP + T2WI	0.827(0.762–0.891)	0.699	0.494	0.984	0.977	0.656	0.812(0.675–0.949)	0.730	0.739	0.714	0.810	0.773
H1 − AP+VP+T2WI	0.823(0.757–0.889)	0.747	0.765	0.721	0.793	0.779	0.736(0.528–0.944)	0.811	0.870	0.714	0.833	0.851
H1 − AP+DP+T2WI	0.841(0.778–0.903)	0.747	0.718	0.787	0.824	0.767	0.814(0.663–0.964)	0.811	1.000	0.500	0.767	0.868
H1 − AP+DP+VP+T2WI	0.819(0.752–0.887)	0.726	0.600	0.902	0.895	0.718	0.734(0.543–0.926)	0.757	0.783	0.714	0.818	0.800
H2 − AP+VP	0.858(0.798–0.918)	0.774	0.694	0.885	0.894	0.781	0.790(0.644–0.937)	0.730	0.609	0.929	0.933	0.737
AP + T2WI + CRH	0.857(0.797–0.918)	0.788	0.894	0.639	0.776	0.831	0.839(0.709–0.968)	0.784	0.696	0.929	0.941	0.800
AP + VP + T2WI + CRH	0.849(0.788–0.911)	0.781	0.847	0.689	0.791	0.818	0.811(0.667–0.954)	0.784	0.739	0.857	0.895	0.810
H1 − AP+T2WI + CRH	0.907(0.858–0.956)	0.884	0.871	0.902	0.925	0.897	0.884(0.773–0.994)	0.838	0.913	0.714	0.840	0.875
H1 − AP+DP+T2WI+CRH	0.852(0.791–0.913)	0.788	0.918	0.607	0.765	0.835	0.851(0.728–0.974)	0.757	0.652	0.929	0.938	0.769
H2 − AP+VP +CRH	0.850(0.789–0.912)	0.774	0.788	0.754	0.817	0.802	0.840(0.711–0.969)	0.784	0.739	0.857	0.895	0.810

Bold values are models with best predictive performance

Abbreviations: CRH, Clinical-Radiologic-Habitat model; AP + T2WI, the radiomics model of total tumor volume in AP and T2WI; H_{1 − AP+T2WI}, the radiomics model of habitat 1 subregion in AP and T2WI; H_2 − AP, the radiomics model of habitat 2 subregion in AP; and so on; AP + T2WI + CRH, the fusion model include the radiomics model of total tumor volume in AP and T2WI and clinical, radiologic, habitat features; H_{1 − AP+T2WI} + CRH, the fusion model include the radiomics model of habitat 1 subregion in AP and T2WI and clinical, radiologic, habitat features