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Table 4 Performance of the WSDL model in HT subgroups

From: A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients

 

Accuracy

Accuracy 95% CI

F1

F1 95% CI

Without ICH

0.686

(0.655,0.721)

0.814

(0.791,0.838)

Asymptomatic ICH

0.619

(0.508,0.73)

0.765

(0.674,0.844)

SICH

0.833

(0.5,1)

0.909

(0.667,1)

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BioMedical Engineering OnLine

ISSN: 1475-925X

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