leduckhai/Sentiment-Reasoning
[ACL 2025 Industry Track, Oral] Sentiment Reasoning for Healthcare
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.
Stars
166
Forks
23
Language
Jupyter Notebook
License
—
Category
Last pushed
Jan 05, 2026
Commits (30d)
0
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