Information fusion in biometric systems, either multimodal or intramodal fusion, usually provides an improvement in recognition performance. This paper presents an improved score-level fusion scheme called boosted sco...Information fusion in biometric systems, either multimodal or intramodal fusion, usually provides an improvement in recognition performance. This paper presents an improved score-level fusion scheme called boosted score fusion. The proposed framework is a two-stage design where an existing fusion algorithm is adopted at the first stage. At the second stage, the weights obtained by the AdaBoost algorithm are utilized to boost the performance of the previously fused results. The experimental results demonstrate that the performance of several score-level fusion methods can be improved by using the presented method.展开更多
目的探讨凝视-面-臂-言语-时间(gaze-face-arm-speech-time,G-FAST)评分对院前急救卒中前循环大血管闭塞(large vessel occlusion in the anterior circulation,aLVO)的诊断价值。方法选取2019年7月至2020年12月北京急救中心直属5个分...目的探讨凝视-面-臂-言语-时间(gaze-face-arm-speech-time,G-FAST)评分对院前急救卒中前循环大血管闭塞(large vessel occlusion in the anterior circulation,aLVO)的诊断价值。方法选取2019年7月至2020年12月北京急救中心直属5个分中心送至宣武医院,且有完整院前G-FAST评分和入院诊断信息的卒中患者,根据缺血性卒中患者是否发生LVO分为LVO和非LVO组,采用ROC曲线分析G-FAST评分对院前卒中急救aLVO的诊断价值。结果纳入患者352例,其中急性缺血性卒中占比69.0%(243/352)。进行大血管评估的急性缺血性卒中患者149例,占急性缺血性卒中的61.3%(149/243);发生aLVO患者61例,占大血管病变评估的40.9%(61/149)、占急性缺血性卒中的25.1%(61/243)。149例大血管评估的急性缺血性卒中患者中,男100例,女49例;年龄18~93岁,平均70.5岁。与非aLVO组相比,aLVO组女性较多,G-FAST评分较高,差异均有统计学意义(P<0.05)。G-FAST≥3分患者的aLVO发生率显著高于G-FAST≤2分者(68.9%比31.1%),差异有统计学意义(P<0.05)。G-FAST评分诊断院前急救卒中aLVO的ROC曲线的AUC为0.675(95%CI:0.589~0.761,P=0.000),G-FAST的cut-off值为2.5分时,灵敏度为72.10%,特异度为58.00%。结论G-FAST评分在院前急救卒中可准确识别急性缺血性患者aLVO,早诊断aLVO将利于急性缺血性患者尽早送至高级别卒中中心。展开更多
基金supported by the“MOST”under Grants No.104-2218-E-468-001 and No.104-2221-E-194-050
文摘Information fusion in biometric systems, either multimodal or intramodal fusion, usually provides an improvement in recognition performance. This paper presents an improved score-level fusion scheme called boosted score fusion. The proposed framework is a two-stage design where an existing fusion algorithm is adopted at the first stage. At the second stage, the weights obtained by the AdaBoost algorithm are utilized to boost the performance of the previously fused results. The experimental results demonstrate that the performance of several score-level fusion methods can be improved by using the presented method.
文摘目的探讨凝视-面-臂-言语-时间(gaze-face-arm-speech-time,G-FAST)评分对院前急救卒中前循环大血管闭塞(large vessel occlusion in the anterior circulation,aLVO)的诊断价值。方法选取2019年7月至2020年12月北京急救中心直属5个分中心送至宣武医院,且有完整院前G-FAST评分和入院诊断信息的卒中患者,根据缺血性卒中患者是否发生LVO分为LVO和非LVO组,采用ROC曲线分析G-FAST评分对院前卒中急救aLVO的诊断价值。结果纳入患者352例,其中急性缺血性卒中占比69.0%(243/352)。进行大血管评估的急性缺血性卒中患者149例,占急性缺血性卒中的61.3%(149/243);发生aLVO患者61例,占大血管病变评估的40.9%(61/149)、占急性缺血性卒中的25.1%(61/243)。149例大血管评估的急性缺血性卒中患者中,男100例,女49例;年龄18~93岁,平均70.5岁。与非aLVO组相比,aLVO组女性较多,G-FAST评分较高,差异均有统计学意义(P<0.05)。G-FAST≥3分患者的aLVO发生率显著高于G-FAST≤2分者(68.9%比31.1%),差异有统计学意义(P<0.05)。G-FAST评分诊断院前急救卒中aLVO的ROC曲线的AUC为0.675(95%CI:0.589~0.761,P=0.000),G-FAST的cut-off值为2.5分时,灵敏度为72.10%,特异度为58.00%。结论G-FAST评分在院前急救卒中可准确识别急性缺血性患者aLVO,早诊断aLVO将利于急性缺血性患者尽早送至高级别卒中中心。
