Evidence map›Paper›PMID 33806409›Full record

ArticleSensors (Basel, Switzerland)2021

Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO

Javier González-Enrique, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso-López, Daniel Urda, Lipika Deka, Ignacio J Turias

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Javier González-EnriqueIntelligent Modelling of Systems Research Group (MIS), Department of Computer Science Engineering, Polytechnic School of Engineering, University of Cádiz, 11204 Algeciras, Spain.ORCID 0000-0002-5765-369X
Juan Jesús Ruiz-AguilarIntelligent Modelling of Systems Research Group (MIS), Department of Industrial and Civil Engineering, Polytechnic School of Engineering, University of Cádiz, 11204 Algeciras, Spain.ORCID 0000-0002-2170-0693
José Antonio Moscoso-LópezIntelligent Modelling of Systems Research Group (MIS), Department of Industrial and Civil Engineering, Polytechnic School of Engineering, University of Cádiz, 11204 Algeciras, Spain.
Daniel UrdaGrupo de Inteligencia Computacional Aplicada (GICAP), Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad de Burgos, Av. Cantabria s/n, 09006 Burgos, Spain.ORCID 0000-0003-2662-798X
Lipika DekaThe De Montfort University Interdisciplinary Group in Intelligent Transport Systems (DIGITS), Department of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK.
Ignacio J TuriasIntelligent Modelling of Systems Research Group (MIS), Department of Computer Science Engineering, Polytechnic School of Engineering, University of Cádiz, 11204 Algeciras, Spain.

Funding

Ministerio de Ciencia e Innovación RTI2018-098160-B-I00Universidad de Cádiz Ayuda para Estancias en Centros de Investigación del Programa de Fomento e Impulso de la actividad Investigadora de la Universidad de Cádiz
6 · The paper itself

Abstract

This study aims to produce accurate predictions of the NO

Indexed as

air pollutionartificial neural networksdeep learningexogenous variablesfeature selectionforecastingLSTMsnitrogen dioxidetime series

Identifiers

PMID33806409
PMCPMC7961900

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.