Evidence map›Paper›PMID 27570833›Full record

ArticleProceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology2011

A Case-based Retrieval System using Natural Language Processing and Population-based Visualization.

William Hsu, Ricky K Taira, Fernando Viñuela, Alex A T Bui

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

William HsuMedical Imaging Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, CA.
Ricky K TairaMedical Imaging Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, CA.
Fernando ViñuelaDivision of Interventional Neuroradiology, Department of Radiological Sciences, University of California, Los Angeles, CA.
Alex A T BuiMedical Imaging Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, CA.

Funding

Toward Individually-tailored Medicine: Probabilistic Models of Cerebral AneurysmsR01EB000362 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUI, ALEX · 2003 to 2012
$5.1M
Data Structuring and Visualization System for Neuro-oncologyR01LM009961 · NLM · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TAIRA, RICKY K. · 2009 to 2010
$1.7M
NIBIB NIH HHS R01 EB000362NLM NIH HHS R01 LM009961
6 · The paper itself

Abstract

Electronic medical records capture large quantities of patient data generated as a result of routine care. Secondary use of this data for clinical research could provide new insights into the evolution of diseases and help assess the effectiveness of available interventions. Unfortunately, the unstructured nature of clinical data hinders a user's ability to understand this data: tools are needed to structure, model, and visualize the data to elucidate patterns in a patient population. We present a case-based retrieval framework that incorporates an extraction tool to identify concepts from clinical reports, a disease model to capture necessary context for interpreting extracted concepts, and a model-driven visualization to facilitate querying and interpretation of the results. We describe how the model is used to group, filter, and retrieve similar cases. We present an application of the framework that aids users in exploring a population of intracranial aneurysm patients.

Indexed as

Case-based retrievalinformation visualizationknowledge reprsentationnatural language processing

Identifiers

PMID27570833
PMCPMC5001495

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Registered trials

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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.