Evidence map›Paper›PMID 31872307›Full record

ArticleJournal of medical systems2019

A Parser to Support the Definition of Access Control Policies and Rules Using Natural Languages.

Marco Rosa, João Paulo Barraca, André Zuquete, Nelson Pacheco Rocha

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2019. 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.

Marco RosaDepartment of Electronic, Telecommunications and Informatics - Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, Campo Universitário de Santiago, Aveiro, 3810-193, Portugal.
João Paulo BarracaDepartment of Electronic, Telecommunications and Informatics - Instituto de Telecomunicações, University of Aveiro, Campo Universitário de Santiago, Aveiro, 3810-193, Portugal.
André ZuqueteDepartment of Electronic, Telecommunications and Informatics - Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, Campo Universitário de Santiago, Aveiro, 3810-193, Portugal.
Nelson Pacheco RochaDepartment of Medical Sciences - Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, Campo Universitário de Santiago, Aveiro, 3810-193, Portugal. npr@ua.pt.ORCID http://orcid.org/0000-0003-3801-7249

Funding

Programa Operacional Competitividade e Internacionalização 017861
6 · The paper itself

Abstract

As a consequence of the epidemiological transition towards non-communicable diseases, integrated care approaches are required, not solely focused on medical purposes, but also on a range of essential activities for the maintenance of the individuals' quality of life. In order to allow the exchange of information, these integrated approaches might be supported by digital platforms, which need to provide trustful environments and to guarantee the integrity of the information exchanged. Therefore, together with mechanisms such as authentication, logging or auditing, the definition of access control policies assumes a paramount importance. This article focuses on the development of a parser as a component of a platform to support the care of community-dwelling older adults, the SOCIAL platform, to allow the definition of access control policies and rules using natural languages.

Indexed as

Natural Language ProcessingQuality of LifeHealth Information ExchangeHumansInformation Storage and RetrievalInformation SystemsLinguisticsSoftwareABACAccess controlFHIRNatural languageParserXACML

Identifiers

What OpenQuestion holds

Textmetadata
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.