‘Information technology is booming, change in healthcare bears on human life and health, and digital medicine is accelerating the industry’s transformation – innovation here is urgent,’ said Xu Huarui, president of Guilin University of Electronic Technology, opening the fifth International Symposium on Image Computing and Digital Medicine in Guilin.
The symposium has long been a frontier venue where engineering, mathematics and medicine meet, and this year’s edition focused on how medical AI gets promoted and applied.
‘In the post-pandemic era, medical AI arrives at the right time. Information and communication networks empower every industry and can support richer health applications,’ said Xu Kun, vice president of Beijing University of Posts and Telecommunications.
From profiling to imaging
The world is entering a new stage driven by AI at its core. A team under Zhang Ping, academician of the Chinese Academy of Engineering at BUPT, developed ‘AI-driven dynamic profiling for major diseases and an efficient remote prevention and treatment system’, selected among 2021’s World Internet Leading Scientific and Technological Achievements. The system advances medical big data processing and intelligent learning optimisation, responding rapidly to critical cases, surfacing key diagnostic evidence, quantifying disease risk factors dynamically and tracking progression accurately.
AI also applies broadly to medical imaging and pathology. Liu Zaiyi, chief physician at Guangdong Provincial People’s Hospital, noted China’s severe shortage of imaging and pathology physicians – AI can lift diagnostic efficiency and precision while cutting doctors’ repetitive work.
Ophthalmology shows the progress: from intelligent reconstruction and analysis of OCT images to electronic gonioscopy and a fundus-imaging platform for common disease diagnosis and prediction, eye-care AI is both diagnosing and teaching.
Neuroimaging still struggles with small samples, low reproducibility and difficult clinical use; Kong Xiangzhen of Zhejiang University argues the fix is multi-centre cooperation building large databases with stable, reliable brain imaging indicators – a general multi-modal, cross-scale phenotyping collection.
Guilin University of Electronic Technology has deployed intelligent assisted diagnosis for liver cancer, diabetic foot ulcers and thyroid disease with local hospitals, serving regional health needs. The consensus among participants: medical and AI fields must co-innovate – this year’s papers span mathematics, electronics, AI, computer science and biomedical engineering applied to digital medicine, exactly the cross-disciplinary fusion the field needs, as honorary chair Linda Petzold, member of both US national academies, put it.
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