In 2025, the domestically developed AI medical system “DeepSeek” has been widely deployed across China’s tertiary hospitals, becoming a vital intelligent assistant in radiology and pathology departments. Jointly developed by leading domestic AI and medical imaging companies, this system is recognized for its rapid and accurate diagnostic assistance capabilities. It is regarded as a crucial technological tool to alleviate medical resource shortages and enhance diagnostic efficiency.
Enhancing Diagnostic Efficiency and Alleviating Resource Pressure
According to the latest data from the National Health Commission, radiology and pathology departments in tertiary hospitals across the country are facing mounting workloads and heavy burdens on medical staff. Utilizing deep learning algorithms, the DeepSeek system can complete intelligent annotations of high-incidence conditions such as pulmonary nodules, cerebral hemorrhage, and breast masses within seconds, assisting physicians in accurately pinpointing suspicious lesions.
“During peak periods of image reading, DeepSeek helps us reduce diagnostic time by 30% to 50%,” said a radiology department director at a top-tier hospital in Beijing. The application of AI systems not only improves work efficiency but also provides young doctors with valuable opportunities for learning and comparative analysis.
Meanwhile, DeepSeek’s deep integration with Electronic Medical Record (EMR) systems and Picture Archiving and Communication Systems (PACS) has established a closed-loop workflow of “AI pre-screening — physician confirmation — consultation support.” It has demonstrated significant advantages in managing high-risk patients and facilitating remote consultations.
Where Are the Boundaries of AI in Healthcare?
Despite the system’s remarkable application results, questions like “Who is accountable for AI misdiagnoses?” and “Can doctors reject AI recommendations?” have become focal points of industry and public concern. Experts emphasize that AI medical systems are still positioned as “decision support tools” from a legal perspective. However, in actual clinical applications, the influence of AI suggestions on physician decisions is deepening.
“AI can assist but cannot replace the final judgment of doctors,” said a legal advisor involved in the DeepSeek project. “Nevertheless, once AI provides an incorrect suggestion, should physicians bear responsibility for ‘trusting AI’? This issue requires clear institutional definitions.”
Furthermore, topics such as compliant data collection, patient privacy protection, algorithm transparency, and explainability have sparked extensive discussions among academia and regulatory authorities. Some doctors worry that a lack of transparency and traceability in AI technology might trigger a new wave of trust crises in doctor-patient relationships.
Accelerated Regulation: Industry Self-Discipline and Standardization Are Key
In response to the ethical and legal challenges faced by AI medical applications, the National Health Commission and the National Medical Products Administration (NMPA) have initiated the formulation of specialized management regulations for AI medical devices. The draft will focus on key areas such as “algorithm validation mechanisms, risk-level management, data privacy compliance, and diagnostic responsibility delineation,” aiming to provide a regulatory framework for the safe and compliant use of AI medical systems.
Meanwhile, industry associations and leading enterprises are also promoting the establishment of an “AI diagnostic decision traceability mechanism” to ensure that every AI-assisted judgment and physician decision-making path is verifiable and auditable.
The Progress and Caution of AI Empowering Healthcare
“The future of AI in healthcare is not about replacing doctors, but empowering them,” experts noted. Systems like DeepSeek will continue to deepen their applications in high-demand, low-complexity scenarios such as lung cancer screening and stroke emergency care. However, in areas involving complex pathological judgments and multidisciplinary collaboration, AI must proceed cautiously in its role as a decision-support tool.
The practical cases of DeepSeek not only demonstrate AI’s immense potential in enhancing medical efficiency but also highlight the tension and dynamics between medical technology and ethical regulations. The future path of AI in healthcare urgently requires the collaborative evolution of technology, legal frameworks, and societal consensus.
