In-hospital mortality risk stratification of Asian ACS patients with artificial intelligence algorithm.
Sazzli KasimSorayya MalekCheen SongWan Azman Wan AhmadAlan Yean-Yip FongKhairul Shafiq IbrahimMuhammad Shahreeza SafiruzFirdaus AzizJia Hui HiewNurulain IbrahimPublished in: PloS one (2022)
ACS patients were better classified using a combination of machine learning and deep learning in a multi-ethnic Asian population when compared to TIMI scoring. Machine learning enables the identification of distinct factors in individual Asian populations to improve mortality prediction. Continuous testing and validation will allow for better risk stratification in the future, potentially altering management and outcomes.
Keyphrases
- machine learning
- artificial intelligence
- deep learning
- big data
- end stage renal disease
- acute coronary syndrome
- ejection fraction
- chronic kidney disease
- newly diagnosed
- prognostic factors
- peritoneal dialysis
- convolutional neural network
- patient reported outcomes
- coronary artery disease
- cardiovascular disease
- current status
- cardiovascular events
- adipose tissue
- bioinformatics analysis