In the intensive care unit of Peking University Shenzhen Hospital, doctors use the Mindray Medical Qiyuan big model to complete the data tracing and integration of the entire diagnosis and treatment process within 5 seconds, generate structured medical records in 1 minute, and press the accelerator button for clinical treatment. At Xi'an North Hospital, the application of AI (artificial intelligence) can compress the imaging diagnosis time of aortic dissection from 15 to 20 minutes to 3 minutes, saving valuable time for saving lives. In lung nodule screening, AI helps radiologists reduce their workload by 30% to 50%, resulting in an overall improvement of 30% in the hospital's imaging diagnosis efficiency and a 42% reduction in average patient waiting time. Currently, AI technology is rapidly evolving and has been widely applied in fields such as imaging, assisted diagnosis, and personalized treatment plan recommendation, indicating that the application of AI in modern medicine has entered the stage of large-scale implementation. Becoming a good assistant for medical staff In the medical scene, AI does not operate alone, but serves as an "assistant" for medical staff, forming a new model of human-machine relay. Hu Min, the person in charge of the Information Center of Xi'an North Hospital, introduced that after completing the imaging examination, the AI assisted imaging diagnosis system can quickly analyze and automatically complete the preliminary screening for patients. For example, in the detection of early breast cancer and occult fracture of ribs, the system will mark suspicious lesions within a few seconds, give quantitative indicators such as size, shape and density, and generate a structured preliminary report. The doctor reviews the AI results based on clinical experience, eliminates false positive lesions, and ultimately makes a diagnosis. In the clinical decision-making process, Northern Hospital has integrated the DeepSeek big model into the doctor workstation. After the doctor takes screenshots of the patient's test report and inputs them, the model will quickly extract key abnormal indicators. Combined with clinical guidelines, it will generate a "result overview+possible diagnosis+need for additional examinations" prompt to help the doctor quickly grasp the condition. The model will combine patient complaints, current medical history, disease course, and other information to propose various treatment plans such as drug selection and precautions. Doctors can make personalized adjustments based on this to form the final plan. AI can also optimize surgical planning. Before surgery, the chief surgeon will import the patient's CT data into the AI surgical planning system, generate a three-dimensional model of the patient's lungs, and clearly display the precise location, infiltration range, and spatial relationship between the tumor and surrounding tissues. During the surgical process, the 3D model can serve as real-time navigation to help doctors gain insight into the progress of the surgery. ”Guo Qing, Deputy Director of the Department of General Surgery and Thoracic Surgery at Northern Hospital, introduced that AI 3D reconstruction technology has achieved a leap from "assessment based extensive anatomy" to "navigation based fine anatomy", helping doctors avoid important organs and blood vessels as much as possible during surgery, and achieving "sub lobectomy" that maximizes the preservation of healthy lung tissue. Sun Hongxia, director of the Imaging Department of the Third Hospital of Wafangdian in Dalian, said that AI can recognize millimeter sized nodules that are difficult for the human eye to distinguish. Its stability beyond experience makes "early cancer signs" nowhere to hide, raising screening sensitivity to a new height. This also allows some patients to seek treatment at their doorstep without having to go to big cities or hospitals. Wafangdian Third Hospital has also introduced artificial intelligence robots to help complex spine surgeries move towards digitization, intelligence, and precision, benefiting more patients. Recently, a 78 year old patient diagnosed with lumbar spinal stenosis and lumbar disc herniation, as well as a 34 year old patient with lumbar vertebral burst fracture, underwent surgery with the assistance of artificial intelligence surgical robots. With the precise positioning function of 3D imaging, the robot assisted system can complete surgical planning in one go and achieve accurate nail placement, making the surgical process more minimally invasive, precise, and safe, bringing better treatment results to patients. AI has also made new progress in the field of traditional Chinese medicine. The Chinese Academy of Traditional Chinese Medicine, in collaboration with Zhongke Wenge, has launched the "Big Medical Golden Chamber Traditional Chinese Medicine Big Model", which gathers more than 1500 classics, over 100000 clinical cases, and over 100 guidelines to construct a fine tuned dataset for traditional Chinese medicine. It has covered various application scenarios such as clinical diagnosis and treatment, health regulation, traditional Chinese medicine education, and research and development of traditional Chinese medicine. However, for cases with extremely rare diseases or multiple intertwined diseases, the matching degree of AI recommendations is still not high. Therefore, at present, the main value of AI is more reflected in 'speeding up+reducing missed diagnosis', rather than surpassing manual judgment in all scenarios. ”Hu Min believes. Expanding the application scenarios of the entire chain Currently, the global AI healthcare industry is in a growth stage of deep technological cultivation and scene differentiation, and the AI applications of modern medicine have entered the stage of large-scale implementation. From a clinical practice perspective, the maturity of AI medical applications presents a pattern of "leading diagnosis and treatment, prevention and follow-up, and rehabilitation starting". In terms of policies, in November 2024, the National Health Commission, the State Administration of Traditional Chinese Medicine, and the National Center for Disease Control and Prevention jointly issued the "Reference Guidelines for Artificial Intelligence Application Scenarios in the Health Industry", which listed 84 typical application scenarios and clarified the status of AI assistance. This fills the gap in industry application standards, effectively avoids problems such as blind development and disorderly application, and promotes more targeted, scientific, and standardized implementation of AI technology in the field of health. In November 2025, the General Office of the National Health Commission, the General Office of the National Development and Reform Commission, the General Office of the Ministry of Industry and Information Technology, the State Administration of Traditional Chinese Medicine, and the National Bureau for Disease Control and Prevention jointly issued the "Implementation Opinions on Promoting and Standardizing the Development of 'Artificial Intelligence+Medical and Health' Applications", proposing that by 2030, the basic coverage of intelligent auxiliary applications in grassroots diagnosis and treatment should be achieved, and the widespread use of artificial intelligence technologies such as medical imaging intelligent auxiliary diagnosis and clinical diagnosis and treatment intelligent decision-making should be promoted in secondary and above hospitals. The standard and regulatory system for 'artificial intelligence+medical and health' applications should be basically improved, and a number of globally leading science and technology innovation and talent training bases should be built. Ning Yuqiang, General Manager of CCID Consulting's Medical and Health Industry Research Center, believes that China's AI healthcare is currently in the stage of large-scale implementation driven by policies. On the one hand, at the technical level, there is a transition from "technology pilot" to "large-scale implementation". According to relevant data from the National Health Commission, in recent years, relying on the construction of county-level medical communities and policy promotion, AI tools have rapidly covered primary healthcare, public health and other scenarios. 80% of counties (cities, districts) have initially established county-level image, electrocardiogram, and laboratory resource sharing centers. By 2025, the number of remote medical imaging diagnosis services in counties will exceed 68 million, and AI has become an important support for grassroots medical services. On the other hand, scenario applications are extending from "single scenario" to "full chain". Ning Yuqiang pointed out that previously, AI healthcare focused on a single step such as initial screening of images. In recent years, its application has gradually extended to the entire chain of "prevention diagnosis and treatment rehabilitation health management". For example, from chronic disease screening to auxiliary diagnosis, prescription review, and then to home rehabilitation guidance, a full process service loop has been formed. At the same time, the rapid development of multimodal AI technology can integrate multi-source data such as images, text, and genomes, promoting the transformation of AI from an "auxiliary tool" to an "intelligent partner", which is more in line with the continuity needs of medical services and significantly enhances the comprehensive value of AI healthcare. At present, the acceptance of AI tools among frontline medical staff is steadily increasing in order to promote the comprehensive upgrading of the industry. According to two consecutive years of research conducted by the American Medical Association from 2023 to 2024, the proportion of doctors using AI has significantly increased, and trust in AI has gradually increased. The core needs are focused on clinical decision support and administrative workload reduction, reflecting a positive and positive shift in global healthcare workers' acceptance of AI. Pang Bo, Vice President of Xiyuan Hospital of Chinese Academy of Traditional Chinese Medicine, pointed out that AI has always been a tool for serving medical practitioners rather than a substitute. AI can optimize resource allocation and also play a certain value in promoting medical research, accelerating drug development, and exploring disease mechanisms. However, in the field of traditional Chinese medicine, due to the difficulty of AI in understanding philosophical concepts such as "syndrome differentiation and treatment" and "holistic concept" of traditional Chinese medicine, the TCM diagnosis and treatment suggestions it outputs often need to be processed by doctors to meet clinical needs. Therefore, some TCM practitioners still hold reservations about the application of AI tools. ”Pang Bo pointed out that there are still differences in the acceptance and adaptability of medical personnel, and the popularization of AI healthcare requires further training and promotion to enhance the trust and application ability of medical personnel towards new technologies. Regarding the widespread concern that AI will replace some job positions, Pang Bo believes that AI will replace some repetitive and standardized positions and functions in the medical field, but will not replace doctors' core diagnosis and treatment decision-making, clinical practice, and humanistic care functions. On the contrary, AI will reshape the structure of medical positions and give rise to a large number of new medical positions such as technology enhanced and human-machine collaboration. In the long run, AI will drive the optimization of medical positions, innovation of medical models, and comprehensive upgrading of public health and lifestyle. With the continuous iteration of technology, AI healthcare will upgrade from a simple auxiliary tool to an industry core empowerment engine, giving rise to diverse medical models and formats such as precision medical teams, remote diagnosis and treatment alliances, and medical research collaboration platforms, promoting the transformation of medical services from single point support to full process and multi-dimensional empowerment. ”Pang Bo said. (New Society)