- AyurVAID Pharmacy
Hours of Operation:
8am – 8pm (Mon-Sat)
8am – 5pm (Sun)
Hours of Operation:
8am – 8pm (Mon-Sat)
8am – 5pm (Sun)
Featured in the Global South AI Health Casebook Launched by WHO India-AI Foundation at India – AI Impact Summit 2026
Apollo AyurVAID’s submission selected for inclusion in the World Health Organization’s and IndiaAI Foundation’s ‘Compendium on the Real-World Impact of AI in Health’.Chosen from submissions across 12 countries, AyurVAID D-RISK is an advanced, non-invasive, self-administered, H2O AutoML Model for detection of undiagnosed diabetics. With 43.6% of Indian diabetics remaining undiagnosed (2023) and with an estimated 650 M. undiagnosed, globally, by 2050, D-RISK addresses a clear and present threat to global health & wellbeing in targeted fashion.
Government of India AI Impact Casebook
Use Case 17
AI for Predictive Analysis in Health
AI Impact Casebooks Showcase
Over 170 deployed and scalable AI innovations across priority sectors:
Diabetes often progresses silently.
Many individuals remain undiagnosed for years
Conventional testing may detect disease after metabolic imbalance is established
Population risk scores may show variable sensitivity across diverse demographics
Large-scale non-invasive screening tools remain limited
AyurVAID D-RISK integrates demographic, anthropometric, lifestyle, and symptom-based indicators, including features derived from classical Ayurveda (traditional medicine) descriptions of early metabolic imbalance, together with machine learning methods. In model-development, datasets of approximately 12,000 individuals, the AutoML-based framework demonstrated moderate-to-high discrimination metrics under cross-validation conditions. D-RISK is intended as a screening and triage support tool to help prioritise individuals for confirmatory laboratory testing. Reported metrics reflect model-development validation results and should not be interpreted as definitive clinical diagnostic performance. The framework illustrates how culturally contextualised, non-invasive risk indicators from Ayurveda across large patient cohorts combined with AI methods may support earlier risk stratification when implemented with clinical oversight and governance safeguards.
Clinical Workflow designed for optimal screening and triage support
Individual completes digital risk assessment
Data processed through AutoML ensemble model
Insights generated with feature contribution analysis
Risk score categorisation computed
Clinician review and interpretation
Referral for confirmatory laboratory testing
AyurVAID D-RISK™ – Use Case 17
Government of India AI Impact Casebook – Health Sector (2026)
At Apollo AyurVAID, we believe the future of healthcare lies in integrating classical medical wisdom with modern artificial intelligence under rigorous clinical governance.
AyurVAID D-RISK™ represents our commitment to culturally contextualised, responsible, AI-enabled healthcare innovation.
Apollo AyurVAID
Innovation & Research Team
Hours of Operation:
8am – 8pm (Mon-Sat)
8am – 5pm (Sun)