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医院相关C. Diff的患者风险分层作为时间序列分类任务Patient Risk Stratification for Hospital-Associated C. Diff as a Time-Series Classification Task |
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| 课程网址: | http://videolectures.net/machine_wiens_patient/ |
| 主讲教师: | Jenna Wiens |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 2013-01-18 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | A patient's risk for adverse events is affected by temporal processes including the nature and timing of diagnostic and therapeutic activities, and the overall evolution of the patient's pathophysiology over time. Yet many investigators ignore this temporal aspect when modeling patient risk, considering only the patient's current or aggregate state. We explore representing patient risk as a time series. In doing so, patient risk stratification becomes a time-series classification task. The task differs from most applications of time-series analysis, like speech processing, since the time series itself must first be extracted. Thus, we begin by defining and extracting approximate \textit{risk processes}, the evolving approximate daily risk of a patient. Once obtained, we use these signals to explore different approaches to time-series classification with the goal of identifying high-risk patterns. We apply the classification to the specific task of identifying patients at risk of testing positive for hospital acquired colonization with \textit{Clostridium Difficile}. We achieve an area under the receiver operating characteristic curve of 0.79 on a held-out set of several hundred patients. Our two-stage approach to risk stratification outperforms classifiers that consider only a patient's current state (p |
| 关 键 词: | 病理生理学; 患者风险; 时间序列 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-05-15：lxf |
| 阅读次数: | 89 |