William J Clinton Foundation: AI-enabled Express Health Camps
Strengthening Early TB Detection by Embedding AI into Government-Led Active Case Finding
.png "12,12,932"){kind=icon}
Watch the story in 60 seconds (AI-generated video; visuals are illustrative)
Case at a Glance
The William J. Clinton Foundation (WJCF) is a not-for-profit organisation supporting government-led health systems to reduce disease burden and save lives. WJCF works closely with the Ministry of Health & Family Welfare and state governments across 16 states, focusing on TB, HIV/AIDS, hepatitis, non-communicable diseases, Ayushman Bharat, and climate health initiatives.
India bears 26% of the global TB burden, yet traditional symptom-based screening fails to detect a large proportion of cases. Limited availability of radiologists, poor care-seeking behaviour, and reliance on manual workflows constrained the effectiveness of community-based Active Case Finding, resulting in missed diagnoses and delayed treatment.
WJCF deployed an AI-enabled Express Health Camp model using ultraportable chest X-ray devices integrated with an offline-first Radiological Information System (RIS). The system enabled instant AI-driven interpretation, beneficiary data capture, and triage at the point of screening without reliance on internet connectivity allowing large-scale, efficient TB detection in low-resource settings.
Key systemic challenges included:
WJCF implemented AI-enabled ultraportable chest X-ray devices across Express Health Camps, integrated through a modular, vendor-agnostic Radiology Information System (RIS). The system captures beneficiary data, stores chest X-ray (CXR) images, runs AI interpretation offline, and generates dashboards and reports for program teams. Role-based access ensures smooth field operations, while instant triage enables immediate referral and follow-up.
Technology Stack
| Tools/ Techniques | Used For | What It Enabled | Category |
|---|---|---|---|
| Radiological Information System (RIS) | Express Health Camps | Offline data capture, AI integration, reporting | Proprietary |
| AI CXR Interpretation Models | Field screening | Instant triage of presumptive TB cases | Commercial |
| Ultraportable CXR Devices | Community screening | Point-of-care imaging | Commercial |
| Dashboards & Reporting Tools | Program management | Data-driven decision-making | Proprietary |
Key Project Learnings
Offline-first systems enabled reliable screening in low-connectivity settings, directly increasing coverage.
AI-led triage reduced dependence on scarce radiologists, accelerating confirmations.
Integrating AI into routine workflows lowered costs while improving yield.
Potential for Wider Adoption
| Sector | Adaptability of the Solution |
| National TB Programs | Scalable deployment for Active Case Finding |
| State Health Departments | Integration into routine screening operations |
| Global Health Programs | Replicable model for high-burden, low-resource settings |
See it in Action
RIS digitizes the beneficiary journey in health camps—from registration to screening and X-ray—enabling eligibility checks, unique IDs, and end-to-end tracking at scale.
Dr. Kajas Shah, CTTB Officer at Andhavar Municipal Corporation, describes how AI-powered X-ray screening transformed their active TB case-finding efforts.