leduckhai/Sentiment-Reasoning

[ACL 2025 Industry Track, Oral] Sentiment Reasoning for Healthcare

41
/ 100
Emerging

This project helps healthcare professionals understand the emotional tone of patient interactions, whether spoken or written. It takes patient transcripts (from speech or text) and produces not only a sentiment label (positive, negative, neutral) but also a clear explanation for that label. This empowers clinicians and care coordinators to better understand the patient's perspective and the underlying reasons for their expressed feelings.

166 stars.

Use this if you need to analyze patient sentiment from conversations or text and want an explanation for the sentiment, not just a label, to improve decision-making in healthcare.

Not ideal if you're looking for general-purpose sentiment analysis outside of healthcare or don't require detailed rationales for sentiment predictions.

healthcare-analytics patient-feedback clinical-communication sentiment-analysis medical-transcription
No License No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 17 / 25

How are scores calculated?

Stars

166

Forks

23

Language

Jupyter Notebook

License

Last pushed

Jan 05, 2026

Commits (30d)

0

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