Evidence map›Paper›PMID 34682000›Full record

ArticleEntropy (Basel, Switzerland)2021

On Building and Evaluating a Medical Records Exploration Interface Using Text Mining Techniques.

Úrsula Torres Parejo, Jesús Roque Campaña, María Amparo Vila, Miguel Delgado

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. 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.

Úrsula Torres ParejoDepartment of Statistics and Operational Research, University of Granada, 18071 Granada, Spain.ORCID 0000-0003-0496-7609
Jesús Roque CampañaDepartment of Computer Science and Artificial Intelligence, University of Granada, 18014 Granada, Spain.ORCID 0000-0002-5820-4095
María Amparo VilaDepartment of Computer Science and Artificial Intelligence, University of Granada, 18014 Granada, Spain.ORCID 0000-0002-2773-3306
Miguel DelgadoDepartment of Computer Science and Artificial Intelligence, University of Granada, 18014 Granada, Spain.ORCID 0000-0001-5333-5179

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical records contain many terms that are difficult to process. Our aim in this study is to allow visual exploration of the information in medical databases where texts present a large number of syntactic variations and abbreviations by using an interface that facilitates content identification, navigation, and information retrieval. We propose the use of multi-term tag clouds as content representation tools and as assistants for browsing and querying tasks. The tag cloud generation is achieved by using a novelty mathematical method that allows related terms to remain grouped together within the tags. To evaluate this proposal, we have carried out a survey over a spanish database with 24,481 records. For this purpose, 23 expert users in the medical field were tasked to test the interface and answer some questions in order to evaluate the generated tag clouds properties. In addition, we obtained a precision of 0.990, a recall of 0.870, and a

Indexed as

content identificationelectronic health recordshealth information systemsknowledge representationvisual interface

Identifiers

PMID34682000
PMCPMC8534415

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.