RecruitingNCT06506318

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

Combining Image-clinical Model Based on Deep Learning and Radiomics to Predict Multidrug-resistant Klebsiella Pneumoniae Liver Abscess


Sponsor

Shengjing Hospital

Enrollment

550 participants

Start Date

Jan 1, 2024

Study Type

OBSERVATIONAL

Conditions

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.


Eligibility

Min Age: 18 Years

Inclusion Criteria2

  • 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 Criteria1

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

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Locations(1)

Shengjing hospital of China medical university

Shenyang, Liaoning, China

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NCT06506318


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