Status:

RECRUITING

A Joint Model Based on Deep Learning to Predict Multidrug-resistant Klebsiella Pneumoniae Liver Abscess

Lead Sponsor:

Shengjing Hospital

Collaborating Sponsors:

The First Affiliated Hospital of China University of Science and Technology (Anhui Provincial)

Guilin Medical University, China

Conditions:

Liver Abscess

Eligibility:

All Genders

18+ years

Brief Summary

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.

Detailed Description

Liver abscess is one of the most common abdominal organ infections worldwide, with a mortality rate that once reached as high as 70%. Before the widespread use of antibiotics, suppurative appendicitis...

Eligibility Criteria

Inclusion

  • 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.

Exclusion

  • Patients diagnosed with other types of liver abscess such as amoeba.

Key Trial Info

Start Date :

January 1 2024

Trial Type :

OBSERVATIONAL

Allocation :

ESTIMATED

End Date :

March 1 2025

Estimated Enrollment :

550 Patients enrolled

Trial Details

Trial ID

NCT06506318

Start Date

January 1 2024

End Date

March 1 2025

Last Update

July 17 2024

Active Locations (1)

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Shengjing hospital of China medical university

Shenyang, Liaoning, China, 110004

A Joint Model Based on Deep Learning to Predict Multidrug-resistant Klebsiella Pneumoniae Liver Abscess | DecenTrialz