Machine learning models predict coagulopathy in spontaneous intracerebral hemorrhage patients in ER.
Fengping ZhuZhiguang PanYing TangPengfei FuSijie ChengWenzhong HouQi ZhangHong HuangYirui SunPublished in: CNS neuroscience & therapeutics (2020)
The constructed models exhibit good prediction accuracy and efficiency. It might be used in clinical practice to facilitate target intervention for acute coagulopathy in patients with spontaneous intracerebral hemorrhage.
Keyphrases
- machine learning
- clinical practice
- brain injury
- end stage renal disease
- randomized controlled trial
- newly diagnosed
- liver failure
- prognostic factors
- wastewater treatment
- respiratory failure
- drug induced
- intensive care unit
- big data
- aortic dissection
- acute respiratory distress syndrome
- extracorporeal membrane oxygenation
- mechanical ventilation