Proteomics is an emerging field of modern biotechnology and an attractive research area in bioinformatics. Protein annotation by mass spectrometry has recently been utilized for the classification and prediction of diseases. In this paper we apply the theory of linear predictive coding and its decision logic for the prediction of major adverse cardiac risk using mass spectra. The new method was tested with a small set of mass spectrometry data. The initial experimental results are found promising for the prediction and show the implication of the potential use of the data for biomarker discovery.
机译:心脏磁共振和实时心肌灌注超声心动图对梗塞质量的比较,可预测ST抬高型心肌梗死再灌注后主要不良心脏事件
机译:血管患者术前B型利钠肽对重大不良心脏事件的预测能力:个别患者数据的荟萃分析。
机译:血管外科手术中主要不良心脏事件的预测:心脏风险评分是否具有实用价值?
机译:线性预测编码及其决策逻辑,可利用质谱数据对重大不良心脏事件进行早期预测
机译:使用数据挖掘技术探索行政数据集中不良事件的医院编码实践。
机译:预测血管外科手术30天内的主要不良心脏事件的发生:使用个体患者数据荟萃分析的最小p值法和ROC曲线法的经验比较
机译:心脏磁共振和实时心肌灌注超声心动图的梗塞物质对比较作为ST升升再灌注后主要不良心动事件的预测因子心肌梗死