MANUSCRIPT: Natural language processing: algorithms and tools to extract computable information from EHRs and from the biomedical literature
The increasing adoption of electronic health records EHRs and the corresponding interest in using these data for quality improvement and research have made it clear that the interpretation of narrative text contained in the records is a critical step. The biomedical literature is another important information source that can benefit from approaches requiring structuring of data contained in narrative text. For the first time, we dedicate an entire issue of JAMIA to biomedical natural language processing NLP, a topic that has been among the most cited in this journal for the past few years. We start with a description of a contest to select the best performing algorithms for detection of temporal relationships in clinical documents see page 806, followed by a general review of significance and brief description of commonly used methods to address this task see page 814.
Written by Brian S McGowan, PhD
Dr. McGowan has served in leadership positions in numerous medical educational organizations and commercial supporters and is a Fellow of the Alliance (FACEhp). He founded the Outcomes Standardization Project, launched and hosted the Alliance Podcast, and most recently launched and hosts the JCEHP Emerging Best Practices in CPD podcast. In 2012 he Co-Founded ArcheMedX, Inc, a healthcare informatics and e-learning company to apply his research in practice.
