Kenya has showcased its use of artificial intelligence (AI)-supported chest X-ray screening to detect tuberculosis (TB), including among people who may not present with conventional symptoms.

🇰🇪 Breaking It Down

Health Principal Secretary Mary Muthoni said Kenya presented its experience at a high-level side event on “Reimagining the Future of Healthcare with AI” held on the sidelines of the 81st United Nations General Assembly.

According to Muthoni, Kenya is integrating AI-supported screening into routine health services as part of efforts to strengthen early detection and expand access to diagnostic services.

“We shared Kenya’s experience in integrating AI-supported screening into routine health services to strengthen early detection and expand access to diagnostics,” the PS said.

📌 What You Need to Know

The technology uses ultra-portable digital chest X-ray machines fitted with Computer-Aided Detection (CAD) software, which uses AI to analyse images of a patient's lungs and identify patterns that may be linked to TB and other lung conditions.

The process starts when a patient undergoes a digital chest X-ray. The image is then analysed by the AI software, which can identify abnormalities and highlight areas that may require further medical assessment.

The AI system can produce an automated risk or abnormality assessment within a short time, allowing health workers to quickly identify patients who may need further testing instead of waiting for a specialist to review every image.

When the system flags a possible TB case, it does not independently confirm that the patient has TB. The patient is instead referred for confirmatory laboratory tests such as GeneXpert or TrueNat before treatment is started.

The technology is particularly useful for finding people who may have TB without the conventional symptoms. This could help health workers identify cases that might otherwise remain undetected until the disease becomes more advanced.

The machines are also portable, allowing them to be moved to health facilities and outreach sites in underserved and hard-to-reach communities where access to specialised diagnostic services may be limited.

📰 Source: Kenyans.co.ke