India carries the world's largest burden of tuberculosis. Despite effective treatment being available, many people with TB are not diagnosed early, either because they have no symptoms or because they cannot easily reach a diagnostic centre. Artificial intelligence, combined with portable X-ray machines, is helping change that. Here is how AI is speeding up TB screening in India and what results have been reported.
Why TB screening is difficult
TB is caused by bacteria that usually affect the lungs. It spreads through the air when people with active TB cough or sneeze. Early diagnosis is crucial, both to treat patients and to stop the spread.
But screening faces several obstacles. Many people with TB do not have obvious symptoms, especially in early stages. Rural and remote areas often lack radiologists to read chest X-rays. Traditional X-ray machines are large and fixed in hospitals. And waiting for test results delays treatment.
How AI helps
Chest X-rays are one of the best tools for spotting signs of TB in the lungs. But reading X-rays requires expertise, and India does not have enough radiologists, especially outside cities.
AI software can analyse a chest X-ray within seconds and flag images that show signs consistent with TB. Health workers can then refer flagged individuals for confirmatory tests, such as molecular tests that detect TB bacteria.
This approach does not replace doctors or laboratory tests. Instead, it helps decide quickly who needs further testing, which makes large-scale screening practical.
Handheld X-ray machines
The other key technology is portable or handheld X-ray machines. These are small, battery-powered devices that can be carried to villages, slums, prisons, workplaces and other community settings. Combined with AI reading, they allow screening to happen where people are, rather than requiring them to travel to a hospital.
The 100-day TB Mukt Bharat campaign
On 7 December 2024, the government launched an intensified 100-day TB Mukt Bharat Abhiyan, focusing on 347 priority districts across the country. According to a written reply in the Rajya Sabha reported in 2025, the campaign made extensive use of portable X-ray machines and AI tools.
The government reported:
- About 12.97 crore people screened.
- 7.19 lakh new TB cases detected, including 2.85 lakh asymptomatic cases, people who had TB but no symptoms.
- More than 13.46 lakh Nikshay Shivirs, community screening and awareness camps, held.
- TB treatment coverage rising from 59 percent to 85 percent.
The detection of 2.85 lakh asymptomatic cases is especially significant. These are people who would likely not have sought testing on their own, but who could spread TB to others. Finding them early helps break the chain of transmission.
The AI tools used
The government has used AI tools validated by the Indian Council of Medical Research, ICMR. These include:
DeepCXR, an AI tool for automated chest X-ray reading, provided free of charge to the government and deployed in several states and union territories under the National TB Elimination Programme.
An AI-based system that automates reading and recording results from Line Probe Assay tests, a laboratory method used to detect drug-resistant TB.
Indian private companies have also developed AI chest X-ray tools used in TB programmes in India and other countries. Qure.ai, for example, has partnered with diagnostic companies to deploy AI-enabled chest X-ray screening for early TB detection.
Why this matters
TB is curable, but delays in diagnosis lead to more severe illness, more deaths and more transmission. AI-assisted screening helps by:
- Finding more cases, including people without symptoms.
- Screening faster, reducing the time from screening to treatment.
- Reaching remote areas through portable machines.
- Reducing the burden on scarce radiologists.
- Making screening more consistent.
India's goal
India set an ambitious goal of eliminating TB ahead of the global Sustainable Development Goal target of 2030. While the TB burden remains high, intensified screening using technology is a key part of the strategy.
Challenges and limitations
AI is not a complete solution. Several challenges remain.
- Confirmation is needed. AI flags possible TB, but confirmatory tests are required for diagnosis.
- False positives and negatives. AI may flag people who do not have TB, or miss some who do.
- Follow-up. Finding cases is only useful if patients start and complete treatment, which can last months.
- Infrastructure. Portable X-ray machines, internet connectivity, trained staff and laboratory capacity are all needed.
- Validation. AI tools must be validated on Indian populations and monitored over time.
- Social factors. Stigma, poverty, malnutrition and access to care affect TB outcomes. Programmes such as Ni-kshay Mitra, which supports patients with nutrition, address some of these factors.
What it means for patients
- If you are offered TB screening in your community, it is quick, and early detection can protect you and your family.
- A flagged X-ray means you need further tests, not that you definitely have TB.
- TB treatment is available free under the national programme.
- Completing the full course of treatment is essential.
The bottom line
AI chest X-ray reading and portable X-ray machines are helping India screen far more people for TB, faster and closer to where they live. The 100-day TB Mukt Bharat campaign reported screening nearly 13 crore people and detecting lakhs of cases, including many without symptoms. AI is not a replacement for confirmatory tests, treatment or social support, but it is proving to be a powerful tool in India's fight against one of its oldest public health challenges.
