Studies in health technology and informatics
Jan 1, 2019
BACKGROUND: In a database of electronic health records, the amount of available information varies widely between patients. In a real-time prediction scenario, a machine learning model may receive limited information for some patients.
Studies in health technology and informatics
Jan 1, 2019
The analysis of primary care data plays an important role in understanding health at an individual and population level. Currently the utilization of computerized medical records is low due to the complexities, heterogeneities and veracity associated...
Studies in health technology and informatics
Jan 1, 2019
Electronic Health Records (EHRs) conceal a hidden knowledge that could be mined with data science tools. This is relevant for N.N. Burdenko Neurosurgery Center taking the advantage of a large EHRs archive collected for a period between 2000 and 2017....
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2019
Electronic phenotyping is the task of ascertaining whether an individual has a medical condition of interest by analyzing their medical record and is foundational in clinical informatics. Increasingly, electronic phenotyping is performed via supervis...
Studies in health technology and informatics
Jan 1, 2019
Information Quality (IQ) is a core tenant of contemporary data management practices. Across many disciplines and industries, it has become a necessary process to improve value and reduce liability in data driven processes. Information quality is a mu...
Studies in health technology and informatics
Jan 1, 2019
EHR-based, computable phenotypes can be leveraged by healthcare organizations and researchers to improve the cohort identification process. The ability to identify patient cohorts using aspects of care and outcomes based on clinical characteristics o...
INTRODUCTION: Identifying occurrences of medication side effects and adverse drug events (ADEs) is an important and challenging task because they are frequently only mentioned in clinical narrative and are not formally reported.
INTRODUCTION: Adverse drug event (ADE) detection is a vital step towards effective pharmacovigilance and prevention of future incidents caused by potentially harmful ADEs. The electronic health records (EHRs) of patients in hospitals contain valuable...
INTRODUCTION: This work describes the Medication and Adverse Drug Events from Electronic Health Records (MADE 1.0) corpus and provides an overview of the MADE 1.0 2018 challenge for extracting medication, indication, and adverse drug events (ADEs) fr...
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