Open AccessDeep Learning-Based Available and Common Clinical-Related Feature Variables Robustly Predict Survival in Community-Acquired Pneumonia
Author(s) -
Ding-Yun Feng,
Yong Ren,
Mei Zhou,
Xiaoling Zou,
Wenbin Wu,
Hailing Yang,
Yuqi Zhou,
Tiantuo Zhang
Publication year - 2021
Publication title -
risk management and healthcare policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.828
H-Index - 22
ISSN - 1179-1594
DOI - 10.2147/rmhp.s317735
Subject(s) - artificial intelligence , community acquired pneumonia , machine learning , deep learning , feature (linguistics) , medicine , pneumonia , feature engineering , artificial neural network , computer science , linguistics , philosophy
Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality worldwide. Although there are many predictors of death for CAP, there are still some limitations. This study aimed to build a simple and accurate model based on available and common clinical-related feature variables for predicting CAP mortality by adopting machine learning techniques.