Learning temporal weights of clinical events using variable importance
نویسندگان
چکیده
منابع مشابه
Learning temporal weights of clinical events using variable importance
BACKGROUND Longitudinal data sources, such as electronic health records (EHRs), are very valuable for monitoring adverse drug events (ADEs). However, ADEs are heavily under-reported in EHRs. Using machine learning algorithms to automatically detect patients that should have had ADEs reported in their health records is an efficient and effective solution. One of the challenges to that end is how...
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ژورنال
عنوان ژورنال: BMC Medical Informatics and Decision Making
سال: 2016
ISSN: 1472-6947
DOI: 10.1186/s12911-016-0311-6