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“Quality Of Reporting In Imaging Studies Applying Artificial Neural Network Models In Cancer Detection” Metadata:

  • Title: ➤  Quality Of Reporting In Imaging Studies Applying Artificial Neural Network Models In Cancer Detection
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Edition Identifiers:

  • Internet Archive ID: osf-registrations-jvem5-v1

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"Quality Of Reporting In Imaging Studies Applying Artificial Neural Network Models In Cancer Detection" Description:

The Internet Archive:

We hope to assess the completeness of reporting, using TRIPOD-AI, in studies leveraging artificial neural networks (ANNs) for cancer screening, detection, and characterisation in medical imaging applications. By evaluating 99 studies, this project aims to identify significant gaps in methodological transparency. Our findings on reporting completeness can inform efforts toe enhance reporting standards and promote model reproducibility. This would ultimately facilitate clinical translation and implementation.

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"Quality Of Reporting In Imaging Studies Applying Artificial Neural Network Models In Cancer Detection" is available for download from The Internet Archive in "data" format, the size of the file-s is: 0.09 Mbs, and the file-s went public at Sun Jun 29 2025.

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  • Source: Internet Archive
  • All Files are Available: Yes
  • Number of Files: 5
  • Number of Available Files: 5
  • Added Date: 2025-06-29 16:00:36
  • Scanner: Internet Archive Python library 1.9.9

Available Files:

1- ZIP

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2- Metadata

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  • File Name: osf-registrations-jvem5-v1_files.xml
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3- Metadata

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  • File Name: osf-registrations-jvem5-v1_meta.sqlite
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  • File Name: osf-registrations-jvem5-v1_meta.xml
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