Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot Study.

Affiliation

Royal Adelaide Hospital, Australia. Electronic address: [Email]

Abstract

Intravenous thrombolysis decision-making and obtaining of consent would be assisted by an individualized risk-benefit ratio. Deep learning (DL) models may be able to assist with this patient selection.

Keywords

Artificial intelligence,Convolutional neural network,Machine learning,Prognostication,

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