The persistent threat of tuberculosis (TB), especially multi-drug-resistant strains, is exacerbated by the COVID-19 pandemic, which has disrupted detection and treatment efforts worldwide.
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Amid this global health crisis, the World Economic Forum cites artificial intelligence (AI) as pivotal in revolutionizing TB diagnostics and counteracting the pandemic's setbacks.
TB is the second deadliest infectious disease, surpassed only by COVID-19, with 4.1 million undiagnosed cases, primarily in India, Indonesia, and the Philippines, due to lockdowns and hindered diagnostic access.
Furthermore, TB-related death reduction globally falls short of the targeted 35% by only achieving a 9.2% decrease.
The End TB Strategy emphasizes early detection, necessitating patient-focused services, robust testing infrastructure, and a skilled workforce.
Despite this, 2021 data showed decreased TB diagnostic and treatment spending. With less than half of the global target funds allocated, AI has surfaced as a vital tool.
Qure.ai, an organization with FDA/CE clearances for chest X-ray detection, has shown promising results in India.
Its AI-powered solution resulted in a 33% increase in TB notifications and decreased patient drop-outs from 72% to 53% at a hospital in Rajasthan.
AI's potential extends beyond TB detection. It can aid early lung cancer diagnosis and treatment, indicating its limitless potential in transforming global healthcare.
