An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study.
Seungseok LeeWu-Seong KangDo Wan KimSang Hyun SeoJoongsuck KimSoon Tak JeongDong-Keon YonJin Seok LeePublished in: Journal of medical Internet research (2023)
Our proposed AI model exhibits remarkable accuracy in predicting ED mortality. Including the necessity for external validation, a large nationwide data set would provide a more accurate model and minimize overfitting. We anticipate that our AI-based risk calculator tool will substantially aid health care providers, particularly regarding triage and early diagnosis for trauma patients.
Keyphrases
- artificial intelligence
- emergency department
- trauma patients
- big data
- machine learning
- healthcare
- deep learning
- end stage renal disease
- newly diagnosed
- chronic kidney disease
- ejection fraction
- high resolution
- peritoneal dialysis
- prognostic factors
- electronic health record
- cardiovascular disease
- type diabetes
- coronary artery disease
- patient reported outcomes
- health insurance
- patient reported