斯坦福的人工智能 预测器官死亡后的存活能力 精确度达到75% 降低移植取消率 Stanford's AI predicts organ viability post-death with 75% accuracy, reducing transplant cancellations.

由斯坦福研究人员开发的一个新的人工智能系统预测,循环系统死亡后的捐赠者是否将满足30至45分钟的关键窗口,以便进行可行的器官恢复、优异的外科医生和降低移植取消率,其精确度达到75%。 A new AI system developed by Stanford researchers predicts with 75% accuracy whether donors after circulatory death will meet the critical 30- to 45-minute window for viable organ recovery, outperforming surgeons and reducing transplant cancellations. 该模型对2,000多例病例进行了培训,利用实时临床数据评估死亡时间,用不完整的记录开展工作,并可以根据医院规程定制。 Trained on over 2,000 cases, the model uses real-time clinical data to assess death timing, works with incomplete records, and can be customized to hospital protocols. 它可以增加可用器官,降低成本,提高移植效率,并有可能扩大到心脏和肺移植。 It may increase usable organs, lower costs, and improve transplant efficiency, with potential expansion to heart and lung transplants.