AI-Powered Tuberculosis Screening Gains Traction in Thailand, Boosting Detection Rates

Thailand is making significant strides in its fight against tuberculosis (TB) by embracing artificial intelligence (AI) to improve detection rates and accelerate progress toward the 2030 global elimination goals. While the country is no longer listed among those with a high burden of drug-resistant TB by the World Health Organization (WHO), it remains a high-burden nation for TB overall and TB-HIV co-infections. A key challenge has been finding the estimated 22,000 people with TB disease who go undiagnosed each year.

Addressing the “Missing Millions”

Historically, TB diagnosis has relied heavily on microscopy, a method known to miss a significant proportion of cases – often more than half of those who test positive. Recognizing this limitation, the 2023 United Nations General Assembly High Level Meeting on TB called for all countries, including Thailand, to transition to WHO-recommended molecular tests for upfront TB testing by 2027.

Thailand is ahead of the curve in this transition. As of 2024, 69% of TB testing in the country utilizes upfront molecular testing, significantly higher than the global average of 54% and the 41% average in the South-East Asian region, according to the latest WHO Global TB Report 2025.

The Rise of AI in TB Screening

Beyond molecular testing, Thailand is pioneering the employ of AI to enhance TB detection. In July 2021, the WHO integrated AI-powered computer-aided detection software into its official guidelines for TB screening and diagnosis, aiming to bridge the gap in detection. This marked the first time AI was officially recommended for interpreting chest X-rays for TB screening.

One such AI solution, Genki AI (developed by DeepTek), was approved by Thailand’s Food and Drug Administration (FDA) in 2022. Genki AI automates the interpretation of chest X-rays, identifying 27 different pathologies, including TB. It has as well received approval from regulatory bodies in the United States, the European Union, Singapore, India, Malaysia, Kenya, and Indonesia.

Real-World Impact at Aikchol Hospital

At Aikchol Hospital in Chonburi province, Thailand, radiologist Dr. Grisit Prueksaritanond has been utilizing Genki AI for over a year. Chonburi province, along with Bangkok, experiences higher TB rates than other regions of Thailand. Dr. Grisit reports that Genki AI has helped him identify at least three cases of TB that would have otherwise been missed, improving diagnostic accuracy.

“Genki AI is crucial. I think it is very helpful,” Dr. Grisit stated. He also highlighted the AI’s ability to detect other lung abnormalities, such as fibrosis, pneumonia, and nodules, enabling more comprehensive patient care.

Benefits Beyond Detection

AI-powered screening offers several advantages, particularly in resource-constrained settings. It can help triage patients, quickly ruling out those without disease and prioritizing those who require further investigation. This is especially valuable in countries like Thailand, where access to radiologists can be limited. AI can also reduce the workload on healthcare professionals, allowing them to focus on complex cases.

Dr. Grisit emphasized that AI can serve as a valuable “second pair of eyes,” even for experienced radiologists, ensuring no abnormalities are overlooked. He also noted that AI can be particularly beneficial in settings where expert readers are scarce.

A Multi-Disease Approach

The WHO is increasingly advocating for a multi-disease elimination approach, and AI supports this strategy. Genki AI’s ability to screen for a range of lung pathologies, not just TB, allows for a more holistic assessment of patient health.

Looking Ahead

With just 56 months remaining to achieve the global goal of ending TB by 2030, Thailand’s commitment to innovation, particularly its adoption of AI-powered screening, offers a ray of hope. Continued investment in these technologies, coupled with a focus on prevention, early diagnosis, and comprehensive care, will be essential to protect populations from TB and achieve the Sustainable Development Goals.