Evidence map›Paper›PMID 36217089›Full record

ArticleAdvances in experimental medicine and biology2022

Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea-Hypopnea Events from the Oximetry Signal.

Fernando Vaquerizo-Villar, Daniel Álvarez, Gonzalo C Gutiérrez-Tobal, C A Arroyo-Domingo, F Del Campo, Roberto Hornero

Abstract read
PubMed Publisher
In one paragraph

Article in Advances in experimental medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

6 authors at 4 institutions in 1 country.

Fernando Vaquerizo-VillarBiomedical Engineering Group, University of Valladolid, Valladolid, Spain. fernando.vaquerizo@gib.tel.uva.es.
Daniel ÁlvarezBiomedical Engineering Group, University of Valladolid, Valladolid, Spain.
Gonzalo C Gutiérrez-TobalBiomedical Engineering Group, University of Valladolid, Valladolid, Spain.
C A Arroyo-DomingoCentro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Valladolid, Spain.
F Del CampoCentro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Valladolid, Spain.
Roberto HorneroBiomedical Engineering Group, University of Valladolid, Valladolid, Spain.
Instituto de Salud Carlos III · ESUniversidad de Valladolid · ESBiomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine · ESHospital Universitario Río Hortega · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Automated analysis of the blood oxygen saturation (SpO

Indexed as

Deep LearningSleep Apnea, ObstructiveSleep Apnea SyndromesAdultHumansNeural Networks, ComputerOximetryOxygenPolysomnographyOxygenApneaApnea–hypopnea index (AHI)Apnea index (AI)Blood oxygen saturation (SpO2)Convolutional neural networks (CNN)Deep learningHypopneaHypopnea index (HI)Obstructive sleep apnea (OSA)Oximetry

Identifiers

PMID36217089
OpenAlexW4304481185

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.