The fight against tuberculosis (TB) in India has reached a crucial phase. With Prime Minister Narendra Modi’s ambitious goal of eliminating TB by 2025, the integration of advanced technologies is vital. However, despite significant progress in AI-powered TB screening tools, challenges remain in their implementation within public health programs.
AI Tools Transforming TB Screening
Recent advancements in artificial intelligence have led to the development of AI-powered screening tools that can enhance TB detection efficiency. Two such notable AI solutions are:
- qXR by Qure.ai
- Genki by DeepTek
Both tools have undergone rigorous assessments for sensitivity (ability to detect TB) and specificity (ability to rule out non-TB cases). qXR has demonstrated over 90% sensitivity and more than 70% specificity, while Genki has shown similar promising results. These AI models are already being deployed at multiple sites across India and globally, showcasing their potential in revolutionizing TB screening.
Health Technology Assessment (HTA) and Regulatory Delays
To integrate new technologies into India’s healthcare system, the Health Technology Assessment India (HTAIn) committee evaluates their cost-effectiveness and efficacy. Both qXR and Genki received positive evaluations, proving their potential for large-scale deployment.
However, the Central TB Division (CTD) has yet to introduce these AI tools into the national TB program. Instead, it has recommended DeepCXR, another AI tool, despite its lack of formal HTA assessment. This delay has caused a disconnect between technological advancements and their practical implementation, slowing down efforts to enhance TB detection.
Challenges in Implementation
Even though DeepCXR has been approved for use, there is limited communication with state health departments about its application. The lack of clarity and coordination hampers the effective integration of AI-driven solutions, delaying improvements in TB screening efficiency.
Cost-Effectiveness of AI in TB Detection
A major advantage of AI-assisted TB screening is its affordability. Studies indicate that:
- qXR costs ₹30 per case
- Genki costs ₹22 per case
These cost-effective solutions can significantly reduce the financial burden of TB screening while improving accuracy and efficiency.
The Role of Chest X-rays in TB Detection
Chest X-rays remain a fundamental tool in detecting TB, especially in cases of presumptive and subclinical TB. AI-powered analysis of chest X-rays enhances speed and accuracy, making it an ideal solution for resource-limited settings.
The Road Ahead
To achieve TB elimination by 2025, India must:
- Accelerate AI integration into national TB screening programs.
- Ensure transparency in regulatory approvals and decision-making.
- Improve communication between the CTD and state health departments.
- Expand AI adoption to strengthen early TB detection and treatment.
While AI tools hold immense promise in transforming TB screening, their effective implementation will determine whether India can meet its ambitious goal of eliminating tuberculosis within the next decade.