Around December 15, 2025, the Rajasthan State Health Department launched a major initiative deploying 29 advanced portable X-ray machines equipped with Artificial Intelligence (AI) to strengthen Tuberculosis (TB) diagnosis, particularly in remote and tribal villages across the state. The portable AI-enabled X-ray machines can rapidly screen individuals for suspected TB, providing near-instantaneous preliminary results without the need for centralised laboratory infrastructure. This is critical for Rajasthan, which reported one of India's highest TB burdens — over 1.7 lakh cases in 2024 — with 89,132 cases recorded in the first half of 2025 alone. The initiative aligns with India's National TB Elimination Programme (NTEP) and the government's target of eliminating TB by 2025 (subsequently revised to 2027), which is ahead of the WHO's global target of 2030. The AI software analyses chest X-rays to flag high-risk patients for confirmatory sputum or CBNAAT tests, enabling front-line health workers (ASHAs, ANMs) to conduct mass screenings at community level. The deployment is especially significant for Rajasthan's vast geography — covering desert, semi-arid, and tribal regions — where fixed radiology infrastructure is sparse. The move demonstrates the state's adoption of digital health technology to bridge healthcare access gaps in underserved communities.
Rajasthan Health Dept Deploys 29 AI-Enabled Portable X-Ray Units to Strengthen TB Diagnosis in Remote Villages
Around December 15, 2025, the Rajasthan State Health Department launched a major initiative deploying 29 advanced portable X-ray machines equipped with Artificial Intelligence (AI) to strengthen Tuberculosis (TB) diagnosis, particularly in remote and tribal villages across the state. The portable AI-enabled X-ray machines can rapidly screen individuals for suspected TB, providing near-instantaneous preliminary results without the need for centralised laboratory infrastructure. This is critical for Rajasthan, which reported one of India's highest TB burdens — over 1.7 lakh cases in 2024 — with 89,132 cases recorded in the first half of 2025 alone. The initiative aligns with India's National TB Elimination Programme (NTEP) and the government's target of eliminating TB by 2025 (subsequently revised to 2027), which is ahead of the WHO's global target of 2030. The AI software analyses chest X-rays to flag high-risk patients for confirmatory sputum or CBNAAT tests, enabling front-line health workers (ASHAs, ANMs) to conduct mass screenings at community level. The deployment is especially significant for Rajasthan's vast geography — covering desert, semi-arid, and tribal regions — where fixed radiology infrastructure is sparse. The move demonstrates the state's adoption of digital health technology to bridge healthcare access gaps in underserved communities.
Key facts
- Rajasthan deployed 29 portable AI-enabled X-ray units for TB diagnosis in remote villages around December 2025.
- AI software analyses chest X-rays and flags high-risk patients for confirmatory CBNAAT tests.
- Rajasthan reported over 1.7 lakh TB cases in 2024 with 89,132 cases in the first half of 2025.
- The initiative aligns with India's National TB Elimination Programme targeting elimination by 2027.
- Front-line workers like ASHAs and ANMs can conduct mass screenings at community level using the machines.
- Deployment is critical for Rajasthan's desert, semi-arid, and tribal regions with sparse radiology infrastructure.
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Which statement is correct about Rajasthan Health Department's deployment of 29 AI-enabled portable X-ray units for TB diagnosis?
Rajasthan introduced 29 AI-powered portable X-ray machines to improve early TB detection in rural, remote and high-risk locations such as brick kilns, jails, mining zones and slums. The model combines digital chest X-rays, computer-aided detection and confirmatory testing so that areas with limited radiology infrastructure can identify suspected TB cases faster.
Frequently asked questions
Why did Rajasthan deploy AI-enabled portable X-ray units specifically for TB diagnosis?
Rajasthan has one of India's highest TB burdens — 1.7 lakh cases in 2024 and 89,132 in the first half of 2025 alone. Many cases go undetected in remote desert, semi-arid, and tribal areas due to lack of radiology infrastructure. AI-enabled portable X-ray units allow frontline workers to screen patients at the community level without needing a centralised laboratory, enabling rapid detection and referral for confirmatory testing.
How does AI software assist in tuberculosis diagnosis using chest X-rays?
The AI software analyses chest X-ray images in near real-time, flagging patterns (such as lung infiltrates, cavities, or nodules) that suggest TB infection. High-risk patients flagged by AI are then referred for confirmatory CBNAAT (Cartridge-Based Nucleic Acid Amplification Test) which provides molecular confirmation of TB. This triage approach reduces the workload on labs and speeds up case identification.
What is the National TB Elimination Programme (NTEP) and what is India's 2027 target?
NTEP (National Tuberculosis Elimination Programme) is India's flagship programme to eliminate TB, guided by the WHO's End TB Strategy. India has set a target to eliminate TB by 2027 — five years ahead of the global target of 2030. The programme involves free diagnosis, treatment, and nutritional support through the Nikshay Poshan Yojana for all TB patients.
What role do ASHA and ANM workers play in the AI X-ray TB screening initiative in Rajasthan?
ASHAs (Accredited Social Health Activists) and ANMs (Auxiliary Nurse Midwives) are the primary frontline health workers in rural and tribal India. Under the Rajasthan initiative, these workers operate the portable AI-enabled X-ray machines at community screenings, health camps, and door-to-door visits — bringing early TB detection directly to high-risk populations in remote areas where specialist doctors are unavailable.
What is CBNAAT and how does it complement AI-based X-ray screening in TB control?
CBNAAT (Cartridge-Based Nucleic Acid Amplification Test) is a molecular diagnostic test that detects TB bacteria and drug resistance (including rifampicin resistance) within 2 hours. In Rajasthan's programme, AI X-ray acts as the first-line screening tool to identify suspected cases, while CBNAAT provides the definitive laboratory confirmation — creating a two-step diagnostic pipeline that is both fast and accurate.
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