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China-Tanzania healthcare cooperation brings AI-powered diagnosis to patients_我的网站

一 |     为回馈广大彩民朋友对我省福利彩票的关心和支持，湖北省福利彩票发行中心决定在全省范围内开展丙午马5元、丙午马10元、丙午马20元面值即开票彩民回馈营销活动，现就有关事项公告如下。    

    This photo taken on May 28, 2026 shows Yuan Gang, a radiologist with the 35th Chinese medical team in Zanzibar, discussing MRI images with local doctors at Mnazi Mmoja Hospital in Zanzibar, Tanzania. (The 35th Chinese medical team in Zanzibar/Handout via Xinhua)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 (AI) 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-time specialist consultations.
For years, Zanzibar's healthcare system has faced challenges in diagnosing complex diseases, particularly because of limited imaging expertise, heavy workloads, and the lack of advanced diagnostic tools, said local physician Haitham Hamudu.
Imaging interpretation, often described as the "eyes" of modern medicine, has been especially constrained by limited expertise, heavy workloads, and a lack of advanced tools, Haitham said.
By linking the hospital's imaging system with the First People's Hospital of Lianyungang in east China's Jiangsu Province, he 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 said. "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, 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 said 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.
In one case, a 56-year-old man with a chronic cough was initially diagnosed with inflammation. Yuan's review, supported by AI analysis, identified four small nodules, including one with high-risk features, prompting closer monitoring and potentially preventing the progression of an early tumor.
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 said.
The hospital and its partner institution in Lianyungang have established regular remote multidisciplinary team consultations, bringing together specialists in neurosurgery, oncology, and other disciplines to jointly review complex cases and develop treatment plans.
"I have never seen this kind of consultation before," said local physician Haitham. "So many experts working together, providing practical solutions. It is very inspiring."
Bao Zengtao, leader of the Chinese medical team, said remote consultations not only improve patient care but also enhance the professional capacity of local healthcare workers.
Yuan added that the ultimate goal is to build a sustainable model that can be expanded across Africa, ensuring more patients have access to accurate diagnosis and timely treatment.
    This file photo taken on Oct. 8, 2025 shows Yuan Gang, a radiologist with the 35th Chinese medical team in Zanzibar, talking with a local resident during a community health outreach activity in Zanzibar, Tanzania. (The 35th Chinese medical team in Zanzibar/Handout via Xinhua)
    This file photo taken on Oct. 8, 2025 shows Yuan Gang, a radiologist with the 35th Chinese medical team in Zanzibar, performing an ultrasound examination on a patient at a local health facility during a community health outreach activity in Zanzibar, Tanzania. (The 35th Chinese medical team in Zanzibar/Handout via Xinhua)
。　　一、活动时间　　自8月18日0时至10月31日24时（以即开票系统实际销售并兑奖的时间为准，如活动经费提前用完，活动于当日24时截止）。　　二、活动规则　　（一）购买8月18日0时至10月31日24日扫描销售的丙午马彩票，中奖者在11月15日24时前兑奖可享回馈福利：5元票中10元奖级赠5元购彩金、10元票中20元奖级赠10元购彩金、20元票中60元奖级赠60元购彩金。　　（二）本次活动时间以销售系统实际销售、兑奖时间为准，相应奖级的中奖者应在规定时间内及时到销售机构指定的地点兑取中奖奖金并获得赠票。符合条件的中奖者未能在规定时间内兑奖的，视为自动放弃赠票权利。

二 | 　　（三）有关活动进展情况敬请关注湖北福彩网及湖北福彩微信公众号。　　特此公告。湖北省福利彩票发行中心2026年8月11日。

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Published on:07:05:25