Research & Development
We utilize Real-World Evidence as the foundation for a new form of pain research. Through systematic listening and strategic cooperations, we identify gaps in care for **those affected** that often remain invisible.
Sentiment Analytics
We decode the emotional dimension of the pain experience:
- Analysis of emotional tonality throughout disease progression.
- Detection of frustration, hope, and psychological distress.
- Measuring resonance to various therapeutic approaches.
Natural Language Processing (NLP)
AI models for structuring unformatted data:
- Automated clustering of pain symptoms.
- Recognizing patterns in the everyday language of **those affected**.
- Semantic analysis of complex patient biographies.
Specialized Analytics
Data-driven validation of life reality:
- Detailed statistics on gaps in healthcare services.
- Predictive analytics for forecasting pain flares.
- Correlation between daily activity and pain intensity.
Academic Research Cooperations
We work closely with universities and develop AI algorithms:
- Identifying fibromyalgia and pain types through machine learning.
- Investigating patient journeys.
- Combining clinical data with real-world data, including social media.
Digital Therapeutics
We develop digital tools for individualized treatment programs:
- Development of medical apps and chatbots.
- Personalized support for the daily lives of **those affected**.
- AI-based guidance for disease management.
The Sentiomet Analytics Process
DATA
Raw Data
(Patient Voice)
(Patient Voice)
NLP
Structuring &
Pattern Recognition
Pattern Recognition
SENT
Emotional
Assessment
Assessment
AI
Specialized Analysis
& Predictions
& Predictions
EVI
Real-World
Evidence
Evidence
Academic Validation
In cooperation with the University of Lausanne, we translate these insights into evidence-based models. Our goal is to develop AI biomarkers that enable the transfer of research data directly into the everyday lives of **those affected**.