Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring
First People's Hospital of Chongqing · Dalian Medical University · +2 more institutions
Abstract
Sepsis remains a leading cause of morbidity and mortality worldwide due to its rapid progression and heterogeneous nature. This review explores the potential of Artificial Intelligence (AI) to transform sepsis management, from early detection to personalized treatment and real-time monitoring. AI, particularly through machine learning (ML) techniques such as random forest models and deep learning algorithms, has shown promise in analyzing electronic health record (EHR) data to identify patterns that enable early sepsis detection. For instance, random forest models have demonstrated high accuracy in predicting sepsis onset in intensive care unit (ICU) patients, while deep learning approaches have been applied…
Citation impact
- FWCI
- 60.23
- Percentile
- 100%
- References
- 140
Authors
7- FLFang Li
First People's Hospital of Chongqing
- SWShengguo Wang
Dalian Medical University, Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University
- ZGZhi Gao
Dalian Medical University, Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University
- MQMa Qing
Dalian Medical University, Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University
- SLShan L. Pan
Dalian Medical University, Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University
Topics & keywords
- Sepsis
- Intensive care medicine
- Medicine
- Computer science
- Internal medicine
- Good health and well-being