Predicting Bacteremia among Septic Patients Based on ED Information by Machine Learning Methods: A Comparative Study.

Vivian GohYu-Jung ChouChing-Chih Lee Mi-Chia MaWilliam Yu Chung WangChia-Hsiang Hsu Chih-Chia Hsieh

Published in: Diagnostics (Basel, Switzerland) (2022)

We established models that provide discrimination in predicting bacteremia among patients with sepsis. The reported results could inspire researchers to adopt ML in their development of prediction algorithms.

Keyphrases

machine learning
end stage renal disease
acute kidney injury
emergency department
ejection fraction
newly diagnosed
chronic kidney disease
deep learning
gram negative
artificial intelligence
big data
health information
multidrug resistant
social media