TB Patients Are Often Reluctant to Get Screened, Treated: AI Could Change This

Know how healthcare AI innovation can transform the battle against Tuberculosis in India.

3 min read
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Purnia, a district in the northern part of Bihar, India, over 300 km from the state capital Patna, faces significant resource challenges, notably in its healthcare infrastructure.

Among its residents is LKP (name withheld), a 62-year-old man with a history of smoking and Tuberculosis (TB). Despite presenting a persistent cough and having undergone treatment for TB in the past, the markings on his chest X-ray were not recognised as a relapse by multiple doctors.

His story highlights the broader struggles faced in a country of over 1.6 billion people.

India's Uphill Battle Against TB

As we commemorate World Tuberculosis Day 2024 on 24 March, it is critical to remember that Tuberculosis (TB) is a highly infectious respiratory disease and a global health concern, afflicting over 10 million individuals each year.

India accounts for a quarter of the global TB burden, with the disease particularly impacting vulnerable and marginalised communities.

It has been observed globally that the disease doesn't merely affect the individual patient, its repercussions extend to families and entire communities. Those afflicted with TB frequently encounter societal stigma, which exacts significant tolls.

Fear of discrimination may cause individuals to avoid getting diagnosed at all. Stigma can also affect treatment adherence, potentially leading to drug resistance and poorer health outcomes.

Prime Minister Narendra Modi has set a target to eliminate TB in India by 2025, five years ahead of the global deadline of 2030.

India's approach against TB includes treatment innovation, technology integration, prevention interventions, and enhancing nutrition and wellness.

Integrating technology can significantly propel the nation's efforts forward. This is critical when considering some of the barriers in screening and treating TB.

How To Improve Screening? Here's Where AI Comes In

When it comes to combating TB, incorporating routine health screenings, including simple X-ray examinations, plays a crucial role.

These screenings can detect TB in its early stages, safeguarding lung health and curbing the disease's transmission.

Across the world, 40 percent of the 3.6 billion imaging tests conducted each year are chest X-rays, due to their effectiveness in identifying cardiopulmonary issues, their affordability, minimal radiation exposure, and straightforward procurement.

The World Health Organization, in 2021, advocated for targeted tuberculosis screenings using chest X-ray examinations for populations at risk.

Considering the high number of chest X-ray analyses and the global challenge of interpreting these tests due to limited human resources, the use of artificial intelligence (AI) is pivotal, especially to detect and prioritise cases.

Take, for example, the story of LKP from Purnia. He eventually sought care at the Christian Medical Centre and Hospital (CMCH) in Purnia, a facility that serves over 110 villages in the area. It is also one of the hospitals where’s AI-powered chest X-ray screening solution – qXR – has been deployed.

LKP's case was particularly notable because when his chest X-ray was analysed by qXR, the AI's findings prompted a re-evaluation of his symptoms by the attending physician.

This led to the accurate diagnosis of acute pulmonary TB, resulting in his immediate admission for treatment.


The Way Forward:Harnessing the Power of AI for Healthcare

As we navigate the era of AI, let us embrace its potential to redefine human lives, particularly in healthcare.

AI solutions are revolutionising mass screening efforts, making population-level screenings more accessible and efficient. It is evident that leveraging technology for population-level screenings is the way forward.

Such solutions exemplify the transformative power of AI in healthcare, especially in resource-constrained settings.

The capability of X-rays to pick up asymptomatic cases is crucial in identifying and treating TB early. Furthermore, AI fast-tracks the screening process, enhancing efficiency and accuracy

Given the target to eliminate TB in India by 2025, rapid scaling of new tools is imperative.

Global tuberculosis experts also acknowledge the pressing necessity for population-wide X-ray screening. With advancements in X-ray technology and the integration of AI for targeted screening, there lies the potential to substantially diminish TB incidence rates.

 There is an urgent call to scale up rapidly, especially in developing and high burden countries. At, we're continuously improving our algorithms to meet the evolving needs of TB programs, focusing on areas such as paediatric TB, silicosis, and post-TB lung disease. With collective efforts and innovative solutions, we can strive towards a TB-free world.

(Dr Shibu Vijayan is the Medical Director, Global Health, at This is an opinion piece and the views expressed above are the author’s own. The Quint neither endorses nor is responsible for the same.)

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