Srinivasan VAIRAVAN,Caitlyn Marie CHIOFOLO,Nicolas Wadih CHBAT
申请号：
US15772135
公开号：
US20180322951A1
申请日:
2016.10.19
申请国别(地区):
US
年份:
2018
代理人:
摘要：
A process and system for determining a minimal, ‘pruned’ version of the known ARDS model is provided that quantifies the risk of ARDS in terms of physiologic response of the patient, eliminating the more subjective and/or therapeutic features currently used by the conventional ARDS models. This approach provides an accurate tracking of ARDS risk modeled only on the patients physiological response and observable reactions, and the decision criteria are selected to provide a positive prediction as soon as possible before an onset of ARDS. In addition, the pruning process also allows the ARDS model to be customized for different medical facility sites using selective combinations of risk factors and rules that yield optimized performance. Additionally, predictions may be provided in cases with missing or outdated data by providing estimates of the missing data, and confidence bounds about the predictions based on the variance of the estimates.
