Artificial intelligence (AI) is transforming industries at breakneck speed, and healthcare stands out as one of its most profoundly impacted sectors. Once regarded as a futuristic experiment, AI in medicine is quickly moving into mainstream clinical practice, equipping doctors with new tools to detect diseases, guide treatments and enhance patient outcomes.

"Physicians worldwide are increasingly viewing AI not as a novelty, but as a collaborator," Professor Xu Chuan from Chongqing Jinfeng Lab stated. He cited cancer care as a prominent example: AI systems can now identify tiny, sesame seed-sized signals on medical scans – lesions that the human eye often fails to spot.

Beyond early detection, these AI tools assist doctors in evaluating complex treatment options by integrating genetic data, lifestyle factors and medical histories. Xu emphasized that this does not replace doctors, but rather strengthens their work. "AI is evolving into a 'super assistant,'" he explained, speeding up diagnosis and boosting doctors' confidence in their decisions.

However, precision and speed should never come at the cost of trust. Developing reliable AI tools hinges on how patient data is collected, protected and shared. Xu pointed out that medical records remain scattered across various systems, with inconsistent formats and quality.

The solution, he noted, lies in standardization: unified protocols for electronic health records, regular data audits and technologies that enable hospitals to jointly train AI algorithms without sharing raw patient data.

China's Reference Guide for AI Application Scenarios in the Healthcare Industry marks progress in this direction, establishing stricter rules for privacy protection and accountability. Under its "dual registration" system, AI developers must obtain approval from both regulatory authorities and hospital ethics committees. Legal responsibilities are also clearly outlined: if an AI algorithm causes harm, developers bear liability; if doctors unquestioningly follow AI recommendations, the responsibility shifts to hospitals.

Looking to the future, Xu envisions AI becoming an integral part of daily health management. Instead of waiting for illness to occur, AI could continuously monitor individual health, identifying risks before symptoms emerge.

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

Such a shift, Xu said, would represent a fundamental rethinking of healthcare: an interconnected system that links homes, communities and hospitals into a seamless network. For rural areas, which often lack access to specialized medical care, this integration could be particularly impactful, bringing world-class medical expertise to village-level facilities. For patients globally, it holds the potential to make healthcare more predictive, personalized and affordable.