In-hospital mortality risk stratification of Asian ACS patients with artificial intelligence algorithm

Conventional risk score for predicting in-hospital mortality following Acute Coronary Syndrome (ACS) is not catered for Asian patients and requires different types of scoring algorithms for STEMI and NSTEMI patients. To derive a single algorithm using deep learning and machine learning for the predi...

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Veröffentlicht in:	PloS one 2022-12, Vol.17 (12), p.e0278944-e0278944
Hauptverfasser:	Kasim, Sazzli, Malek, Sorayya, Song, Cheen, Wan Ahmad, Wan Azman, Fong, Alan, Ibrahim, Khairul Shafiq, Safiruz, Muhammad Shahreeza, Aziz, Firdaus, Hiew, Jia Hui, Ibrahim, Nurulain
Format:	Artikel
Sprache:	eng
Schlagworte:	Acute coronary syndrome Acute Coronary Syndrome - diagnosis Acute Coronary Syndrome - epidemiology Acute coronary syndromes Algorithms Analysis Artificial Intelligence Biology and Life Sciences Cardiovascular disease Cardiovascular diseases Care and treatment Clinical medicine Clinical practice guidelines Computer and Information Sciences Coronary vessels Datasets Deep learning Diagnosis Feature selection Health risks Heart Heart rate Hospital Mortality Humans Hypoglycemia Learning algorithms Machine learning Medical prognosis Medicine and Health Sciences Missing data Modelling Mortality Myocardial Infarction Patients Performance prediction Physical Sciences Predictions Research and Analysis Methods Risk Risk Assessment Risk Factors Risk groups ST Elevation Myocardial Infarction Support vector machines Survival Thrombolysis Variables
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