Zanzibar's healthcare improved by Chinese expertise

DAR ES SALAAM — In a radiology room at Lumumba Regional Hospital in Tanzania's Zanzibar, a quiet technological shift is reshaping how doctors detect disease, make decisions, and save lives.

On the island, artificial intelligence systems are helping doctors interpret medical images, while remote consultations connect local physicians with specialists thousands of kilometers away.

Bridging this distance is Yuan Gang, a radiologist with the 35th Chinese medical team in Zanzibar, who combines local imaging, cloud-based AI analysis and real-ime specialist consultations.

For years, Zanzibar's healthcare system has faced challenges in diagnosing complex diseases, particularly because of limited imaging expertise, heavy workloads and a lack of advanced diagnostic tools, according to local physician Haitham Hamudu.

Imaging interpretation, often described as the "eyes" of modern medicine, has been especially constrained, Hamudu says.

By linking the hospital's imaging system with the First People's Hospital of Lianyungang in East China's Jiangsu province, Yuan has introduced a three-layer diagnostic approach, which includes initial reading by local doctors, AI-assisted detection and classification, and quality control through Chinese specialist review.

This hybrid model is enabling doctors in Zanzibar to access the precision and standards of top-tier Chinese hospitals without requiring patients to leave the island.

"Technology is allowing us to overcome distance and resource gaps," Yuan says. "It is not just about solving one case, but about building a system that improves care for many patients."

One of the most striking cases involved a young Zanzibari child suffering from recurrent vomiting and lethargy.

After reviewing the child's magnetic resonance imaging scans, Yuan diagnosed hydrocephalus but found the underlying cause unclear. He immediately initiated a remote consultation with neuroradiology experts in the Chinese city of Lianyungang.

By jointly reviewing the imaging data and clinical records, the team identified the hidden cause, and provided a precise diagnosis and treatment recommendations, giving local doctors a clear path forward and the child a renewed chance at recovery.

Beyond individual cases, Yuan has introduced AI-powered imaging tools to improve diagnostic accuracy in Zanzibar.

He says many women have dense breast tissue, making breast cancer harder to detect with conventional mammography. AI-assisted mammography now analyzes images, classifies lesions using the internationally recognized Breast Imaging Reporting and Data System, and helps doctors assess malignancy risk.

In one case, a 42-year-old woman with mild breast pain showed no obvious abnormalities on routine examination. AI, however, detected two hidden nodules and accurately classified their risk, helping doctors avoid unnecessary procedures while ensuring timely follow-up.

Similarly, AI-assisted lung imaging is improving the early detection of pulmonary nodules that are often missed in manual readings.

Beyond diagnosis, Yuan is helping local doctors adopt AI tools, standardized reporting systems, and structured diagnostic methods through hands-on training and case-based teaching, improving diagnostic accuracy while strengthening local capacity.

The AI imaging initiative is part of a broader digital healthcare partnership between China and Tanzania's Zanzibar, Yuan says.

XINHUA