Deep learning survival model predicts outcome after intracerebral hemorrhage from initial CT scan.
Yutong ChenCyprien A RivierSamantha A MoraVictor Torres LopezSam PayabvashKevin N ShethAndreas HarloffGuido J FalconeJonathan RosandErnst MayerhoferChristopher D AndersonPublished in: European stroke journal (2024)
We developed a generalizable deep learning model to predict onset of dependent living and disability after ICH, which could help to guide treatment decisions, advise relatives in the acute setting, optimize rehabilitation strategies, and anticipate long-term care needs.
Keyphrases
- deep learning
- long term care
- computed tomography
- convolutional neural network
- liver failure
- artificial intelligence
- machine learning
- brain injury
- multiple sclerosis
- dual energy
- magnetic resonance imaging
- respiratory failure
- intensive care unit
- contrast enhanced
- positron emission tomography
- free survival
- replacement therapy
- mechanical ventilation