Actively Recruiting
A Joint Model Based on Deep Learning to Predict Multidrug-resistant Klebsiella Pneumoniae Liver Abscess
Led by Shengjing Hospital · Updated on 2024-07-17
550
Participants Needed
1
Research Sites
60 weeks
Total Duration
On this page
Sponsors
S
Shengjing Hospital
Lead Sponsor
T
The First Affiliated Hospital of China University of Science and Technology (Anhui Provincial)
Collaborating Sponsor
AI-Summary
What this Trial Is About
The goal of this observational study is to train a deep learning-based model to predict multidrug-resistant Klebsiella pneumoniae liver abscess and evaluate it on a multi-center database.
CONDITIONS
Official Title
A Joint Model Based on Deep Learning to Predict Multidrug-resistant Klebsiella Pneumoniae Liver Abscess
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Patients diagnosed as pyogenic liver abscess and was proved by surgery or interventional process.
- Patients had accepted abdominal enhance CT scans before surgery or interventional process.
You will not qualify if you...
- Patients diagnosed with other types of liver abscess such as amoeba.
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Shengjing hospital of China medical university
Shenyang, Liaoning, China, 110004
Actively Recruiting
Research Team
Z
Zhihui Chang
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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