# Real-Time Prediction of Sepsis in Critical Trauma Patients: Machine Learning–Based Modeling Study

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/real-time-prediction-of-sepsis-in-critical-trauma-patients-machine-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jiang Li,Fengchan Xi,Wenkui Yu,Chuanrui Sun,Xiling Wang |
| Citations | 41 |
| DOI | 10.2196/42452 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://jmir.org/api/download?alt_name=formative_v7i1e42452_app4.pdf&filename=1a36e810029ace6bbc8c55a214a8cafb.pdf |
| OpenAlex ID | https://openalex.org/W4362470802 |
| PMID | 37000488 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Fengchan Xi](https://scholariq.org/researchers/fengchan-xi/)

## Paper journal

- [JMIR Formative Research](https://scholariq.org/journals/jmir-formative-research/)

## Paper primary topic

- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)

## Paper topics

- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)
- [Trauma and Emergency Care Studies](https://scholariq.org/topics/trauma-and-emergency-care-studies/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.