Clinical Data for Differentiated Thyroid Cancer Recurrence Analysis

Patient records for thyroid disease research contain demographic, clinical, and treatment outcome attributes. The dataset was created by authors Borzooei, S., Briganti, G., Golparian, M., Lechien, J. R., & Tarokhian, A. as part of research in AI and Medicine, with licensing from UCI and Hamadan University of Medical Sciences.

Use Cases

• Predict disease recurrence based on demographic factors, TNM staging, and risk categorization.
• Analyze treatment response relationships with clinical findings like thyroid function and radiotherapy history.
• Model risk factors for poor outcomes using features such as smoking history, pathology, and focality.

Strengths

• Contains a range of clinical attributes including TNM staging, risk categorization, and recurrence status.
• Explicitly states no missing values, which may simplify analysis.
• Includes binary, categorical, and numeric data types covering patient demographics, history, and examination findings.

Limitations

• Row count and file size are unknown, limiting suitability assessment for large-scale modeling.
• Column-level documentation beyond the listed attribute names is absent; field semantics may require further inspection.
• Last update date is unknown; freshness unverified.

Provenance

Source

OpenML, with authors affiliated with Hamadan University of Medical Sciences.

Collection Method

Part of research in AI and Medicine; likely collected from clinical settings.

Time Range

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Freshness

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Geography

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