Objective: To review the current development of artificial intelligence (AI) technology in the field of transfusion medicine. Methods: A systematic search was conducted in the Clarivate Web of Science Database from inception to December 2024 for literature related to AI and transfusion. A total of 4 775 publications were identified. Based on inclusion and exclusion criteria, 133 original studies were ultimately included and analyzed using a narrative synthesis approach. Results: Research on AI in transfusion has surged since 2020 (accounting for 77% of all publications), with China ranking second globally in publication volume. Among the included studies, 69.2% focused on predicting individual transfusion needs, followed by inventory management (8.3%), diagnosis and prediction of adverse transfusion reactions (6.0%), factors influencing transfusion outcomes (5.3%), blood group identification (5.3%), blood quality testing (4.5%), and precise blood volume measurement (1.5%). Additionally, 4.5% of the studies were published in journals with an impact factor greater than 10; 19.5% developed software or applications; 31.5% were multi-center studies; 48.1% utilized decision tree methods, while 31.5% employed neural network approaches; and 14.2% conducted external validation of the algorithms. Conclusion: AI demonstrates significant potential in transfusion risk prediction, decision support, and blood management. However, challenges remain, including limited model generalizability, insufficient algorithm interpretability, and barriers to clinical translation. The deep integration of AI with transfusion medicine will accelerate the advent of precision transfusion era, maximizing blood resource utilization, reducing waste, and ensuring transfusion safety.

Objective:To measure the beam stability of the electron FLASH radiotherapy accelerator developed by the Institute of Applied Electronics of Chinese Academy of Engineering Physics and to evaluate the performance of scintillator, fast current sensor (FCT) and graphite under the electron FLASH beam.Methods:Each continuous beam exit deviation and each pulse deviation at the electron FLASH radiotherapy accelerator in the same working state were measured. The correlation among three monitors and the measured dose of the accelerator at different electron beam energy (controlled by changing the charging voltage) and different beam pulse numbers were compared, which were validated by a Monte Carlo simulation procedure.Results:At the first high pressure, the first 10 scintillators and FCT signals were relatively large, approximately 2% deviation compared with the average value of 400 pulses. Among 40 beam outflows, the deviation between each pulse was within ±5%. In the accelerator steady state, each beam outflow deviation was within ±1%. Both simulated and measured values showed that the monitor could not be used for dose monitoring at different electron beam energy. However, when the energy was the same, only the number of beam pulses was changed, and linear relationship was observed between the number of the three monitors and the dose measured by the film (all R 2 > 0.999). Conclusions:The beam deviation of each beam outflow of this electron FLASH accelerator is within ±1%. Under the stability of the accelerator beam, the scintillator, FCT and graphite can meet the dose monitoring of the target area, which can provide reference for dose monitoring for subsequent biological experiments.

A total of 12 imported falciparum malaria cases in Yangzhou City in recent years were investigated retrospectively and analysed stafisticaly.All the faleiparum malaria patients returned from malaria endemic area in Africa.No prevalence peak occurred and the symptoms in some patients were not typical.It is necessary to enhance health education for expoaed workers.

Objective:To determine the content of ginsenoside R g1 ,R e and Paeoniflorin by HPLC in Shenshao tablet.Methods: HPLC Symmetry C 18 column was used and CH 3CN H 3PO 4 (11∶89) as mobile phase. The flow rate was 0.8mL/min, the column temperature at 30 ?C and the detective wavelength 203nm and 230nm. Results:The content of ginsenoside R g1 ,R e, and paeoniflorin can be determined by HPLC. The linear concentration ranges of these compound were 0.960?g～4.800?g, 0.912?g～4.560?g,1.050?g～ 5.250 ?g. The average recoveries were 105.2%, 98.5% and 103.5%, respectively.Conclusion: This method is simple and accurate and can be used to determine the content of Shenshao Tablet.