Identifying acute ischemic stroke patients within the thrombolytic treatment window using deep learning.
Jennifer S PolsonHaoyue ZhangKambiz NaelNoriko SalamonBryan Y YooSuzie El-SadenSidney StarkmanNamkug KimDong-Wha KangWilliam F SpeierCorey W ArnoldPublished in: Journal of neuroimaging : official journal of the American Society of Neuroimaging (2022)
Our model achieved higher generalization performance on external evaluation datasets than the current state-of-the-art for TSS classification. These results demonstrate the potential of automatic assessment of onset time from imaging without the need for expertly trained radiologists.
Keyphrases
- acute ischemic stroke
- deep learning
- machine learning
- artificial intelligence
- end stage renal disease
- ejection fraction
- newly diagnosed
- high resolution
- prognostic factors
- pulmonary embolism
- peritoneal dialysis
- convolutional neural network
- resistance training
- human health
- risk assessment
- neural network
- body composition