blood; injuries; learning (artificial intelligence); lung; medical computing; patient treatment; sensitivity analysis; AUC; RUSBoost; TACO; TRALI; blood components; blood transfusion; ensemble learning approach; machine learning base models; majority voting; resampling-boosting combination algorithm; transfusion decision; transfusion-associated circulatory overload; transfusion-related acute lung injury; transfusion-related fatalities; Analytical models; Blood; Boosting; Medical services; Prediction algorithms; Predictive models; Training;
机译:胸腰椎融合手术中输血的发生率,预测因素和术后并发症:来自美国外科医生学院国家外科手术质量改善计划数据库的13695名患者的分析
机译:评估青少年特发性脊柱侧弯后路关节固定术中输血量的比率,预测因素和并发症
机译:全髋关节和膝关节置换术中输血的预测因素和并发症
机译:集合学习方法预测输血并发症
机译:术后出血的趋势和重要预测因子,需要肾癌患者输血的肾病患者
机译:综合学习方法预测输血并发症
机译:新认可或新的输血传播感染。挑战,临床医生面临的输血专家,肯定需要刷新血液银行能力和临床方法