| Application | Example Use Case |
|---|---|
| Clinical Decision Support | Diagnosing diseases based on unstructured EHR notes |
| Enhancing Patient Experience | Analyzing feedback from satisfaction surveys |
| Fraud Detection & Compliance | Spotting irregular claim patterns |
| Medical Research | Analyzing drug trial reports and academic literature |
| EHR Analysis | Structuring handwritten or dictated doctor notes |
Vikash568
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| | Feature | Text Analytics | Sentiment Analysis | | |
| |------------------|--------------------------------------|----------------------------------------| | |
| | Focus | Topics, keywords, word relationships | Emotions behind the words | | |
| | Use Cases | Identify trends, themes, issues | Understand tone, satisfaction, urgency | | |
| | Output Example | “Returns” spiking 40% this week | Sentiment score dropped from +2 to –2 | | |
| | Technology | NLP for structure and grammar | Emotion and tone scoring models | | |
| | Bonus Capability | Finds trending topics and anomalies | Detects mood in text, audio, or video | |