Drug Reviews for Depression, Arthritis, and Birth Control with Aspect and Sentiment Labels

A dataset of patient-generated drug reviews annotated for Aspect Term Extraction and Polarity Detection. The data was created by Gunjan Ansari using an automated, expert-driven rule-based annotation scheme called ATEdrug and was last updated on April 9, 2026. The dataset is focused on three medical conditions: Depression, Arthritis, and Birth control.

Use Cases

• Training models for Aspect Term Extraction based on annotated drug reviews.
• Conducting Polarity Detection (sentiment analysis) on patient opinions about drugs.
• Benchmarking transformer-based models like BERT, BioBERT, and ClinicalBERT for clinical NLP tasks.
• Studying patient-reported outcomes for the specific conditions of Depression, Arthritis, and Birth control.

Strengths

• Dataset is publicly available under a CC-BY-4.0 license.
• Annotation was validated through manual evaluation and annotator agreement.
• The dataset is tailored for three specific medical conditions, providing focused clinical context.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating a limited scope.

Provenance

Source

figshare, author Gunjan Ansari.

Collection Method

Created using an automated, expert-driven rule-based annotation scheme (ATEdrug) with minimal human intervention.

Time Range

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Freshness

Last updated 2026-04-09 17:35:09; freshness should be verified.

Geography

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