ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2003
Medical problem and document model for natural language understanding.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Aligning Structured and Unstructured Medical Problems Using UMLS.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2010Article
- Automation of a problem list using natural language processing.BMC medical informatics and decision making · 2005Article
- Comparing natural language processing tools to extract medical problems from narrative text.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2005Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We are developing tools to help maintain a complete, accurate and timely problem list within a general purpose Electronic Medical Record system. As a part of this project, we have designed a system to automatically retrieve medical problems from free-text documents. Here we describe an information model based on XML (eXtensible Markup Language) and compliant with the CDA (Clinical Document Architecture). This model is used to ease the exchange of clinical data between the Natural Language Understanding application that retrieves potential problems from narrative document, and the problem list management application.
Indexed as
Identifiers
14728214PMC1479970What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.