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) 。
B | 但布达佩斯世锦赛,全红婵的“水花消失术”只在207C“失灵”,三场比赛得分64.35、62.70和61.05。和陈芋汐相比,她每跳一次207C相差14分以上,最高分差到了31.35分,纵使拼命追赶也难以逆转。再加上陈芋汐有两个3.3高难度系数的动作,动作难度分值略高,全红婵只有一个3.3的动作,每个动作都容不得失误。难怪业内教练一直强调,207C难度大,运动员的专项能力一定要匹配得上技术要求,要始终狠抓基本功,否则比赛时的动作稳定性就会打折扣。其实拦住全红婵的不仅仅是207C,还有生长发育期。从东京奥运会至今,全红婵的身高涨高了近10厘米,这对她的体能提出了更高的要求,而陈芋汐自从2019年光州世锦赛夺冠后一直在经历克服身体发育的状态起伏。进入2022年,在三次队内测验中,陈芋汐赢了两次。15岁的全红婵在世锦赛巅峰对决后自我剖析:“我的207发挥不是很好,回国后好好练。
C | ”不到17岁的陈芋汐认为:“我也没有发挥出应有的状态,还要继续完善自己。” 说完后,小姐俩相视一笑,她们还将并肩战斗双人10米台。207C,也将继续考验中国女台小将们。
Current article:http://www.liawucunsainantaonao.sbs/news/20260826_3792796.pptx