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AI-Driven Prediction of Hospital-Acquired Infections With EHR
Sponsor: The Eye Hospital of Wenzhou Medical University
Summary
This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for identifying and diagnosing infection, leveraging multimodal health data.
Official title: Predicting Hospital-Acquired Infections Using Electronic Health Records: An AI-Assisted Approach
Key Details
Gender
All
Age Range
0 Years - 90 Years
Study Type
OBSERVATIONAL
Enrollment
1000000
Start Date
2023-02-01
Completion Date
2025-05
Last Updated
2025-04-17
Healthy Volunteers
Yes
Conditions
Interventions
AI-Based Diagnostic and Prognostic Model
This intervention involves an AI system that integrates multimodal data, including patient medical history, laboratory test results, clinical observations, and treatment data, to predict the risk of hospital-acquired infections (HAIs). The system uses deep learning algorithms to provide real-time, accurate predictions, enabling early identification of patients at risk for infections. By analyzing historical health data, the model aims to predict potential infection developments, improving early detection, prevention strategies, and patient outcomes in hospital settings.
Locations (2)
First Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China
Second Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China