Microbiome Insights: How AI Detects LARS Patterns

The gut microbiome plays a crucial role in digestion, immune response, and overall health. However, for LARS (Low Anterior Resection Syndrome) survivors, microbiome imbalances often worsen symptoms like urgency, incontinence, and bloating. Despite these connections, most LARS treatment approaches don’t focus on microbiome health—that’s where Sanjeevani AI comes in.

At Sanjeevani AI, we use advanced AI-driven microbiome analysis to uncover patterns and predict symptom severity. By analyzing gut bacteria composition, we can develop personalized intervention strategies to help LARS survivors regain control over their digestive health.

Key Insights from Our Pre-Pilot Data

🔹 75% of LARS patients show reduced levels of Butyricicoccus, a beneficial gut bacterium linked to reduced inflammation and better stool consistency.

🔹 AI-powered clustering achieves 82% accuracy in symptom-based patient segmentation, allowing us to personalize treatment recommendations.

Why This Matters

Traditional treatments for LARS often use a one-size-fits-all approach, but every patient’s gut microbiome is unique. By leveraging AI, we can develop data-driven, precision-based interventions that improve symptoms more effectively than generic treatments.

Next Steps: The Sanjeevani AI Pilot Study

To validate our AI model and refine our treatment strategies, we are launching a $50K pilot study involving 10 LARS patients over 90 days. This study will track:

✅ Microbiome diversity changes

✅ Symptom severity reduction

✅ Quality of life (QOL) improvements

📩 Interested in contributing to our research or joining the pilot? Contact us at support@sanjeevaniai.com