Research & Field Notes
Observations, pilot findings, and work-in-progress documentation from building AI clinical intelligence for rural India.
Our Research Mission
To systematically investigate and address the fundamental gaps in rural healthcare delivery — starting with the clinical feedback loop.
📓 Research Notes & Field Findings
Initial observations from our ongoing research pilot in East Champaran. These are working notes, not final papers.
The Clinical Feedback Gap
Why rural doctors never learn if their diagnoses were right — and how missing outcome data causes late disease detection.
Differential Diagnosis vs Pattern Recognition
How seeing 40-50 similar patients daily creates cognitive bias, and how AI can expand diagnostic consideration sets.
Barriers to AI Adoption in Rural Practice
Findings from interviews with 50+ doctors in Bihar — trust, workflow, and language barriers.
Clinical Amnesia: India's Broken Feedback Loop
A working paper on how rural primary care operates without outcome data — and the consequences for late disease detection.
🔬 Research Focus Areas
Clinical Decision Support
Tools to enhance diagnostic accuracy and reduce cognitive load for rural practitioners.
Feedback Systems
Designing closed-loop feedback mechanisms between primary care and outcomes.
Rural Healthcare Access
Barriers to specialist consultation and diagnostics in remote settings.
AI in Primary Care
Responsible AI applications for expanding differential diagnosis in resource-constrained settings.
📋 Current Research Pilot
East Champaran, Bihar (5 clinics)
15 general practitioners
Diagnostic patterns, feedback loop efficacy
January 2026 — Ongoing
Initial observations: Doctors consider 2-3 diagnoses on average without AI support, and receive outcome feedback for <5% of patients. Pilot aims to establish baseline and measure AI impact.
Collaborate on Research
We welcome collaboration with healthcare institutions, researchers, and practitioners interested in systemic healthcare improvement.
📧 Contact Research Team