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Predicting ARDS using the MIMIC II physiological database

机译:使用MIMIC II生理数据库预测ARDS

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Acute Respiratory Distress Syndrome (ARDS) is a critical lung condition occurring in ill patients. Like many other cardiac disorders, ARDS can be assessed by physiological measurements. This study aims to predict ARDS in hospitalized patients using only physiological signals as heart rate and breathing rate. An approach based on hypothesis testing is developed to detect whether subjects' signals deviate from their initial states. The approach is applied on mechanically ventilated subjects in the MIMIC II database. As results, a sensitivity going up to 85% is achieved, with a prediction remaining possible before 24 hours of ARDS occurrence.
机译:急性呼吸窘迫综合症(ARDS)是在病人中发生的一种严重的肺部疾病。像许多其他心脏疾病一样,ARDS可以通过生理测量来评估。本研究旨在仅使用生理信号作为心率和呼吸率来预测住院患者的ARDS。开发了一种基于假设检验的方法来检测受试者的信号是否偏离其初始状态。该方法适用于MIMIC II数据库中的机械通气对象。结果,灵敏度达到了85%,在ARDS发生24小时之前仍然有可能进行预测。

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