Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review.

ABSTRACT:

Background

Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the secondary use of electronic health records (EHRs), where patient data are analyzed to conduct clinical and translational research. Methods based on machine learning to process EHRs are resulting in improved understanding of patient clinical trajectories and chronic disease risk prediction, creating a unique opportunity to derive previously unknown clinical insights. However, a wealth of clinical histories remains locked behind clinical narratives in free-form text. Consequently, unlocking the full potential of EHR data is contingent on the development of

SUBMITTER: Sheikhalishahi S 

PROVIDER: S-EPMC6528438 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature