论文标题
使用结合器早期检测败血症
Early Detection of Sepsis using Ensemblers
论文作者
论文摘要
本文描述了一种通过分析小时患者记录来提前检测败血症的方法。 Physionet 2019挑战包括40,000多名患者的病历。使用插补和薄弱的结合器技术来分析这些医疗记录和3倍验证，在内部创建和验证了模型。该模型的精度为93.45％，实用程序得分为0.271。组织者定义的公用事业分数考虑到了真正的阳性，负面警报和虚假警报。
This paper describes a methodology to detect sepsis ahead of time by analyzing hourly patient records. The Physionet 2019 challenge consists of medical records of over 40,000 patients. Using imputation and weak ensembler technique to analyze these medical records and 3-fold validation, a model is created and validated internally. The model achieved an accuracy of 93.45% and a utility score of 0.271. The utility score as defined by the organizers takes into account true positives, negatives and false alarms.
