CRVIA-Example: De-Identified Pancreatic Cancer Vascular Invasion Assessment Data

2.2 GB of de-identified clinical data supporting a multi-centre study on intelligent pancreatic cancer vascular invasion assessment. The dataset, authored by Xiaohua Qian, was last updated on 2026-04-26 and is shared under a CC-BY-4.0 license. It likely contains patient records and imaging-derived features from a retrospective study.

Use Cases

• Training machine learning models for pancreatic cancer vascular invasion assessment based on clinical and imaging features.
• Validating AI-assisted diagnostic tools in a multi-centre clinical study context.
• Conducting retrospective analysis of factors influencing pancreatic cancer staging and treatment planning.

Strengths

• Data originates from a multi-centre clinical study, suggesting diverse patient sources.
• The 2.2 GB file size indicates a substantial volume of clinical information.
• Dataset is de-identified, which is a standard practice for sharing sensitive clinical data.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Xiaohua Qian, via figshare.

Collection Method

Retrospective, multi-centre clinical study.

Freshness

Last updated 2026-04-26 11:57:53; freshness should be verified.