Hemodialysis is the primary treatment for end-stage renal disease patients, but its mortality rate is still unacceptably high. Based on multi-modality examination data of 63,499 patients from 333medical centers, we developed a Hemodialysis Early Warning and Intervention Copilot (HEWIC) system. This system assists healthcare professionals in identifying hemodialysis patients at high risk of mortality and provides risk factors to makeintervention decisions jointly with healthcare professionals. On the retrospective cohort, HEWICachieved ROC-AUC scores of 0.82and 0.79 on one-month and three-month mortality probability prediction, respectively. We then conducted a pragmatic clinical trial (RCT, ChiCTR2100052662) to evaluate whether HEWIC could assist healthcare professionals in intervention to reduce the mortality rate of hemodialysis patients in the real world. Involving 9,965 hemodialysis patients (5,216 intervention and 4,749 control) from 58 dialysis centers, the trial indicates that HEWIC’s high-risk patient identification and treatment recommendation can help reduce the three-month mortality rate of hemodialysis patients by 38.3%, with a more pronounced effect in primary hospitals. Patients managed by the intervention group (where professionals assisted by HEWIC) received more types of drug treatment and showed varying degrees of improvement in anemia, blood pressure, blood lipids, electrolytes, and inflammatory conditions, thanthe control group. Furthermore, HEWICdoes not require additional time investment from healthcare professionals, nor does it interfere with their clinical work. This study proves that the AI-copilot system not only can benefit hemodialysis treatment but also enhance the standardization of medical care across different regions. Additionally, it also suggests that the human-AIcollaborationframework has the potential to revolutionize clinical diagnosis and treatment practice for other diseases.