Chongqing – AI is reshaping industries at lightning speed—and healthcare is proving one of its most transformative arenas. Bridging News recently spoke online with Prof. Xu Chuan of Chongqing Jinfeng Lab about the opportunities and challenges ahead.

Once seen as a futuristic experiment, AI in medicine is rapidly shifting into mainstream practice, offering doctors new tools to detect disease, guide treatment, and improve patient outcomes.

"Doctors around the world are beginning to see AI less as a novelty and more as a partner," Xu said. He pointed to cancer care as a clear example: AI systems are now able to detect signals as small as a sesame seed on medical scans—lesions that human eyes might easily miss. 

Beyond early detection, these systems help physicians weigh complex treatment choices by integrating genetic data, lifestyle factors, and medical history. The result, Xu argued, is not replacement but reinforcement. "AI is becoming a super assistant," he said, accelerating diagnosis and giving doctors greater confidence in their decisions.

Still, precision and speed cannot come at the expense of trust. Building reliable AI tools depends on how patient data is collected, protected, and shared. Xu noted that medical records remain scattered across different systems, often inconsistent in format and quality. 

The solution, he said, lies in harmonization: unified standards for electronic records, regular data audits, and technologies that allow hospitals to train algorithms collaboratively without exchanging raw patient files.

China's Reference Guide for AI Application Scenarios in the Healthcare Industry is a step in that direction, setting stricter requirements around privacy and accountability. Under its "double registration" system, AI developers must gain approval from both regulators and hospital ethics committees. Legal responsibility is also clearly defined: if an algorithm causes harm, developers are held liable; if doctors follow AI advice uncritically, accountability shifts to hospitals.

Looking ahead, Xu envisions AI quietly weaving itself into daily health management. Instead of waiting until illness strikes, AI could monitor individual health continuously, flagging risks before symptoms appear. 

Virtual hospitals may soon provide remote consultations as accurate as in-person visits, while AI-assisted rehabilitation programs could guide patients through recovery at home. Chronic diseases—long a costly burden for healthcare systems—could be tracked in real time, with treatment plans automatically adjusted to prevent emergencies.

Such a shift, Xu said, would amount to a fundamental reimagining of healthcare: an interconnected system linking homes, communities, and hospitals into a seamless network. For rural areas, often underserved by specialists, this integration could prove especially powerful, extending world-class medical expertise to the village level. And for patients everywhere, it holds the promise of making healthcare more predictive, more personalized, and more affordable.