健康信息学
败血症
计算机科学
机器学习
医学
人工智能
内科学
公共卫生
护理部
作者
Md. Sohanur Rahman,Khandaker Reajul Islam,Johayra Prithula,Jaya Kumar,Mufti Mahmud,M Fasihul Alam,Mamun Bin Ibne Reaz,Abdulrahman Alqahtani,Muhammad E. H. Chowdhury
标识
DOI:10.1186/s12911-024-02655-4
摘要
Sepsis poses a critical threat to hospitalized patients, particularly those in the Intensive Care Unit (ICU). Rapid identification of Sepsis is crucial for improving survival rates. Machine learning techniques offer advantages over traditional methods for predicting outcomes. This study aimed to develop a prognostic model using a Stacking-based Meta-Classifier to predict 30-day mortality risks in Sepsis-3 patients from the MIMIC-III database.
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