Introduction:
Chest X-rays are vital in diagnosing a range of thoracic diseases including tuberculosis (TB), pneumonia, lung cancer, and heart failure. With the evolution of medical imaging, traditional film-based X-rays have transitioned to digital chest X-rays (dCXR), offering faster image acquisition, better storage, and enhanced diagnostic capabilities through Artificial Intelligence (AI).
While digital X-rays are now common, challenges such as overlapping anatomical structures, image quality variability, and interpretation delays remain. AI-enhanced image analysis addresses these gaps by enabling automated, accurate, and faster diagnoses, especially crucial for resource-limited settings.
In Kirinyaga County, the deployment of AI-powered digital X-ray technology is transforming TB detection by enabling early diagnosis, increasing case detection rates, and extending diagnostic services to underserved communities through mobile outreach.
Despite national TB control efforts, Kenya continues to face a high burden of undiagnosed TB. According to the 2016 Kenya TB Prevalence Survey, nearly 50% of TB cases went undiagnosed, particularly among asymptomatic individuals and vulnerable groups such as, prison inmates, People living with HIV (PLHIV), young adults, urban dwellers, elderly (65+), health workers and marginalized and remote populations. The lack of accessible and timely diagnostic tools delayed treatment initiation, increased community transmission, and sustained TB as the leading infectious disease killer globally.
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