Evidence map›Paper›PMID 33233826›Full record

ArticleInternational journal of environmental research and public health2020

A Methodology Based on Expert Systems for the Early Detection and Prevention of Hypoxemic Clinical Cases.

Alberto Comesaña-Campos, Manuel Casal-Guisande, Jorge Cerqueiro-Pequeño, José-Benito Bouza-Rodríguez

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.3field-weighted citation impact, top 9% of its field
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

8 citing papers in PubMed, 22 citations in OpenAlex.

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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 at 1 institution in 1 country.

Alberto Comesaña-CamposDepartment of Design in Engineering, University of Vigo, 36208 Vigo, Galicia, Spain.ORCID 0000-0002-3409-8996
Manuel Casal-GuisandeDepartment of Design in Engineering, University of Vigo, 36208 Vigo, Galicia, Spain.ORCID 0000-0003-1494-8145
Jorge Cerqueiro-PequeñoDepartment of Design in Engineering, University of Vigo, 36208 Vigo, Galicia, Spain.ORCID 0000-0001-8617-595X
José-Benito Bouza-RodríguezDepartment of Design in Engineering, University of Vigo, 36208 Vigo, Galicia, Spain.ORCID 0000-0002-1235-7264
Universidade de Vigo · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Respiratory diseases are currently considered to be amongst the most frequent causes of death and disability worldwide, and even more so during the year 2020 because of the COVID-19 global pandemic. Aiming to reduce the impact of these diseases, in this work a methodology is developed that allows the early detection and prevention of potential hypoxemic clinical cases in patients vulnerable to respiratory diseases. Starting from the methodology proposed by the authors in a previous work and grounded in the definition of a set of expert systems, the methodology can generate alerts about the patient's hypoxemic status by means of the interpretation and combination of data coming both from physical measurements and from the considerations of health professionals. A concurrent set of Mamdani-type fuzzy-logic inference systems allows the collecting and processing of information, thus determining a final alert associated with the measurement of the global hypoxemic risk. This new methodology has been tested experimentally, producing positive results so far from the viewpoint of time reduction in the detection of a blood oxygen saturation deficit condition, thus implicitly improving the consequent treatment options and reducing the potential adverse effects on the patient's health.

Indexed as

Expert SystemsCOVID-19Fuzzy LogicHumansHypoxiacoronavirus disease 2019 (COVID-19)decision support systemsdesign science researchexpert systemshypoxemiamedical algorithmrespiratory diseases

Identifiers

PMID33233826
PMCPMC7699904
OpenAlexW3106243257

What OpenQuestion holds

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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.