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Clinical Trial Summary

Application of artificial intelligence deep learning algorithm to analyze the relationship between hormone sensitivity of idiopathic interstitial pneumonia and imaging features of high resolution CT.


Clinical Trial Description

Methods: the medical records and chest high-resolution CT images of patients with idiopathic interstitial pneumonia admitted to the respiratory department of the Third Hospital of Peking University from June 1, 2012 to December 31, 2020 were retrospectively analyzed.Application of artificial intelligence deep learning neural convolution network method to create recognition technology of different imaging features.Including ground glass, mesh, honeycomb, nodule or consolidation, the model was established. IIP patients were divided into hormone sensitive group and hormone insensitive group according to whether the use of hormone was effective or not.Logistic regression analysis was used to analyze the correlation between statistically significant parameters and hormone sensitivity.Artificial intelligence was used to establish the correlation model between imaging features and clinical data and hormone sensitivity. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05146934
Study type Observational
Source Peking University Third Hospital
Contact
Status Completed
Phase
Start date December 30, 2019
Completion date June 30, 2021

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