Thane: In line with India’s mission to eradicate tuberculosis (TB) by 2025, Thane district has initiated the use of AI-powered X-ray machines for immediate TB diagnosis.
This initiative, which began recently, has already resulted in 85 patients being screened using this technology in Shahapur, Murbad, and Bhiwandi talukas over the past two months.
The effort is part of a broader campaign that includes TB awareness and active case finding. The health team – including ASHA workers, Anganwadi sevikas, and health assistants – has been working at the grassroots level to identify suspected TB cases.
The AI-enabled X-ray technology is now enhancing these efforts by significantly reducing TB diagnosis time and allowing faster initiation of treatment.
The introduction of this technology comes under the directive of Thane Zilla Parishad’s Chief Executive Officer, Rohan Ghuge, who has advocated for the use of artificial intelligence in health services to improve efficiency and transparency.
The AI-based handheld X-ray device is battery-operated, portable, and capable of being used even in remote tribal areas, which makes it particularly useful in a district like Thane that includes hard-to-reach regions.
According to District Health Officer Dr. Gangadhar Parge, the AI tool analyses chest X-rays for early TB diagnosis and connects with a laptop to digitize the images, which can then be reviewed online by a doctor.
This allows for early detection – even when symptoms are minimal—leading to timely treatment and preventing further transmission.
Officials highlight that TB remains a significant public health challenge, with lakhs of new cases reported nationwide every year.
In response, the central government has launched aggressive policies, including screening campaigns and community-level awareness efforts. Maharashtra has been running its own TB eradication programme since 1998.
AI-Based TB Diagnosis: Cost-Effective
The district health department notes that the AI-based diagnosis system is cost-effective and improves both patient outcomes and the reach of health services. The 85 patients identified using this method have already begun receiving appropriate treatment.
