Search AMIA.org

Negation is a linguistic phenomenon that marks the absence of an entity or event. Negated events are frequently reported in both biological literature and clinical notes. Text mining applications benefit from the detection of negation and its scope. However, due to the complexity of language, identifying the scope of negation in a sentence is not a trivial task.

The author discusses the challenges of pharmacovigilance using electronic medical record and claims data. Use of ICD-9 encoded data has low sensitivity for detection of adverse drug events (ADEs), because it requires that an ADE escalate to major-complaint level before it can be identified, and because clinical symptomatology is relatively under-represented in ICD-9. A more appropriate vocabulary for ADE identification, SNOMED CT, awaits wider deployment. The narrative-text record of progress [...]

Medication errors are a major source of morbidity and mortality. Inadequate laboratory monitoring of high-risk medications after initial prescription is a medical error that contributes to preventable adverse drug events. Health information technology (HIT)-based clinical decision support may improve patient safety by improving the laboratory monitoring of high-risk medications, but the effectiveness of such interventions is unclear. Therefore, the authors conducted a systematic review to identify studies that evaluate the [...]

Advances in clinical and translational science, along with related national-scale policy and funding mechanisms, have provided significant opportunities for the advancement of applied clinical research informatics (CRI) and translational bioinformatics (TBI). Such efforts are primarily oriented to application and infrastructure development and are critical to the conduct of clinical and translational research. However, they often come at the expense of the foundational CRI and TBI research needed to grow these [...]

Standardized surveillance syndromes do not exist but would facilitate sharing data among surveillance systems and comparing the accuracy of existing systems. The objective of this study was to create reference syndrome definitions from a consensus of investigators who currently have or are building syndromic surveillance systems.

There is significant interest in leveraging the electronic medical record (EMR) to conduct genome-wide association studies (GWAS).

This article describes a system developed for the 2009 i2b2 Medication Extraction Challenge. The purpose of this challenge is to extract medication information from hospital discharge summaries.

Medication information comprises a most valuable source of data in clinical records. This paper describes use of a cascade of machine learners that automatically extract medication information from clinical records.

The Third i2b2 Workshop on Natural Language Processing Challenges for Clinical Records focused on the identification of medications, their dosages, modes (routes) of administration, frequencies, durations, and reasons for administration in discharge summaries. This challenge is referred to as the medication challenge. For the medication challenge, i2b2 released detailed annotation guidelines along with a set of annotated discharge summaries. Twenty teams representing 23 organizations and nine countries participated in the [...]

We aim to build and evaluate an open-source natural language processing system for information extraction from electronic medical record clinical free-text. We describe and evaluate our system, the clinical Text Analysis and Knowledge Extraction System (cTAKES), released open-source at http://www.ohnlp.org. The cTAKES builds on existing open-source technologies-the Unstructured Information Management Architecture framework and OpenNLP natural language processing toolkit. Its components, specifically trained for the clinical domain, create rich linguistic and [...]