Evidence map›Paper›PMID 36620509›Full record

ArticleHealth science reports2023

Evaluation of effective features in the diagnosis of Covid-19 infection from routine blood tests with multilayer perceptron neural network: A cross-sectional study.

Fatemeh Mohammadi, Leila Dehbozorgi, Hamid Reza Akbari-Hasanjani, Zahra Joz Abbasalian, Reza Akbari-Hasanjani, Reza Sabbaghi-Nadooshan, Hedieh Moradi Tabriz

Open access · goldAbstract read
In one paragraph

Article in Health science reports, 2023. 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
1.8field-weighted citation impact, top 16% 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

3 citing papers in PubMed, 8 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

7 authors at 3 institutions in 1 country.

Fatemeh MohammadiDepartment of Pathology, Sina Clinical-Research Center Tehran University of Medical Sciences Tehran Iran.
Leila DehbozorgiDepartment of Electrical Engineering, Central Tehran Branch Islamic Azad University Tehran Iran.
Hamid Reza Akbari-HasanjaniDepartment of Analytical Chemistry, School of Chemistry Damghan University Damghan Iran.ORCID 0000-0001-9132-071X
Zahra Joz AbbasalianDepartment of Pathology, Sina Clinical-Research Center Tehran University of Medical Sciences Tehran Iran.
Reza Akbari-HasanjaniDepartment of Electrical Engineering, Central Tehran Branch Islamic Azad University Tehran Iran.
Reza Sabbaghi-NadooshanDepartment of Electrical Engineering, Central Tehran Branch Islamic Azad University Tehran Iran.
Hedieh Moradi TabrizDepartment of Pathology, Sina Clinical-Research Center Tehran University of Medical Sciences Tehran Iran.
Islamic Azad University Central Tehran Branch · IRSina Hospital · IRDamghan University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: Coronavirus is an infectious disease that is now known as an epidemic, early and accurate diagnosis helps the patient receive more care. The aim of this study is to investigate Covid-19 using blood tests and multilayer perceptron neural network and affective factors in improving and preventing Covid-19. Methods: This cross-sectional study was performed on 200 patients referred to Sina Hospital, Tehran, Iran, who were confirmed cases of Covid-19 by computerized tomography-scan analysis between 2 March 2020 to 5 April 2020. After verification of lung involvement, blood sampling was done to separate the sera for C-reactive protein (CRP), magnesium (Mg), lymphocyte percentage, and vitamin D analysis in healthy and unhealthy people. Blood samples from healthy and sick people were applied to the multilayer perceptron network for 70% of the data for training and 30% for testing. Result: By examining the features, it was found that in patients with Covid-19, there was a significant relationship between increased CRP and decreased lymphocyte levels, and increased Mg ( Conclusion: The important advantage of using a multilayer perceptron neural network is to speed up the diagnosis and treatment.

Indexed as

blood testcoronavirusCovid‐19multilayer perceptron networkneural network

Identifiers

PMID36620509
PMCPMC9817491
OpenAlexW4313641680

What OpenQuestion holds

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LicenceCC BY
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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.