Evidence map›Paper›PMID 35873626›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

Deep Neural Networks for Optimal Selection of Features Related to Flu.

B Tarakeswara Rao, V N Lakshmana Kumar, D Padmapriya, Kumud Pant, Tejaswini B, Wadi B Alonazi, Khalid M A Almutairi, D Raj, Ramesh Shahabadkar

RetractedOpen access · hybridAbstract readRetracted Publication
PubMed Full text at PMC Publisher
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-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, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Retracted: Deep Neural Networks for Optimal Selection of Features Related to Flu.Evidence-based complementary and alternative medicine : eCAM · 2023
    Article
4 · The record

Corrections and comments

  • Retraction · 2023-08-09Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/48F4C203C74F9B29CE4303E08745BA
  • Retracted
5 · Who and what money

Authors and funding

9 authors at 5 institutions in 4 countries.

B Tarakeswara RaoDepartment of Computer Science & Engineering, Kallam Haranadhareddy Institute of Technology, Dasaripalem, Andhra Pradesh 522019, India.
V N Lakshmana KumarDepartment of Electronics and Communication Engineering, M.V.G.R.College of Engineering (Autonomous), Vizianagaram, Andhra Pradesh 535005, India.
D PadmapriyaDepartment of Electronics and Communication Engineering, Panimalar Engineering College, Chennai, Tamil Nadu 600123, India.
Kumud PantDepartment of Biotechnology, Graphic Era Deemed to Be University, Dehradun, Uttarakhand 248002, India.
Tejaswini BDepartment of Information Science and Engineering, East Point College of Engineering and Technology, Bengaluru, Karnataka 560049, India.
Wadi B AlonaziHealth Administration Department, College of Business Administration, King Saud University, P.O. Box. 71115, Riyadh 11587, Saudi Arabia.
Khalid M A AlmutairiDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box. 10219, Riyadh 11433, Saudi Arabia.
D RajZoonosis Research Center, School of Medicine, Wonkwang University, Iksan, Republic of Korea.
Ramesh ShahabadkarDepartment of Electrical and Computer Engineering, Ambo University, Woliso Campus, Waliso, Ethiopia.ORCID https://orcid.org/0000-0003-1458-349X
King Saud University · SAAmbo University · ETGraphic Era University · INMaharaj Vijayaram Gajapathi Raj College of Engineering · INWonkwang University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent times, humans who have been exposed to influenza A viruses (IAV) may not become hostile. Despite the fact that KLRD1 has been discovered as an influenza susceptibility biomarker, it remains to be seen if pre-exposure host gene expression can predict flu symptoms. In this paper, we enable the examination of flu using deep neural networks from input human gene expression datasets with various subtype viruses. This study enables the utilization of these datasets to forecast the spread of flu and can provide the necessary steps to eradicate the flu. The simulation is conducted to test the efficiency of the model in predicting the spread against various input datasets. The results of the simulation show that the proposed method offers a better prediction ability of 2.98% more than other existing methods in finding the spread of flu.

Identifiers

PMID35873626
PMCPMC9303164
OpenAlexW4285494126

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.