Dharma is a novel, interpretable machine learning based clinical decision support system, designed to address the diagnostic and prognostic challenges of pediatric appendicitis by integrating easily obtainable clinical, laboratory, and radiological data into a unified, real-time predictive framework.
Note: Input 0 if the value is not available or not applicable.
To be used by healthcare professionals only.
LITERATURE: doi:
10.1101/2025.05.27.25328468
EXPLORE Dharma:
GitHub Repository Link
PERFORMANCE METRICS:
Threshold: 64%
AUC-ROC: 0.97-0.98
Sensitivity: 89%-95%
Specificity: 88%-98%
Positive Predictive Value: 93%-99%
Negative Predictive Value: 86%-91%
If appendix not visualized or USG unavailable:
AUC-ROC: 0.95
Threshold: 47% | High Likelihood
Specificity: 97% | PPV: 90%
Threshold: 37% | Probable
Specificity: 92% | NPV: 93%
Threshold: 30% | Possible
Sensitivity: 92%
Less than 30%: Low Likelihood
NPV: 95%
Conceptualized, Designed, and Developed by:
Dr. Anup Thapa, MBBS
Founder: DharmaAI
Sincere gratitude to the team of DharmaAI and my dear friends:
Er. Subash Pahari:
Web-app Development and Deployment
Thank you for introducing me to the wonders of coding and AI,
and for your invaluable mentorship and support.
You are not just a great friend, but also a guiding force in
this project.