Evidence map›Paper›PMID 36518809›Full record

ArticleComputational intelligence and neuroscience2022

Autoencoder Networks Decipher the Association between Lung Cancer and Alzheimer's Disease.

Jialin Li, Xinliang Gao, Mingbo Tang, Chi Wang, Wei Liu, Suyan Tian

Open access · hybridAbstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. 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
0.3field-weighted citation impact, top 43% 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, 5 citations in OpenAlex.

  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 at 2 institutions in 2 countries.

Jialin LiDepartment of Thoracic Surgery, The First Hospital of Jilin University, 1 Xinmin Street, Changchun, Jilin 130021, China.ORCID https://orcid.org/0000-0002-8541-2797
Xinliang GaoDepartment of Thoracic Surgery, The First Hospital of Jilin University, 1 Xinmin Street, Changchun, Jilin 130021, China.ORCID https://orcid.org/0000-0002-6951-4785
Mingbo TangDepartment of Thoracic Surgery, The First Hospital of Jilin University, 1 Xinmin Street, Changchun, Jilin 130021, China.ORCID https://orcid.org/0000-0001-5097-0644
Chi WangDepartment of Internal Medicine, College of Medicine, Markey Cancer Center, University of Kentucky, 800 Rose Street, Lexington, KY 40536, USA.
Wei LiuDepartment of Thoracic Surgery, The First Hospital of Jilin University, 1 Xinmin Street, Changchun, Jilin 130021, China.ORCID https://orcid.org/0000-0002-0980-7818
Suyan TianDivision of Clinical Research, The First Hospital of Jilin University, 1 Xinmin Street, Changchun, Jilin 130021, China.ORCID https://orcid.org/0000-0002-5942-1542
Jilin University · CNUniversity of Kentucky · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the most common malignancy and is responsible for the largest cancer-related mortality worldwide. Alzheimer's disease is a degenerative neurological disease that burdens healthcare worldwide. While the two diseases are distinct, several transcriptomic studies have demonstrated they are linked. However, no concordant conclusion on how they are associated has been drawn. Since these studies utilized conventional bioinformatics methods, such as the differentially expressed gene (DEG) analysis, it is naturally expected that the proportion of DEGs having either the same or inverse directions in lung cancer and Alzheimer's disease is substantial. This raises the inconsistency. Therefore, a novel bioinformatics method capable of determining the direction of association is desirable. In this study, the moderated

Indexed as

Alzheimer DiseaseLung NeoplasmsComputational BiologyGene Expression ProfilingHumans

Identifiers

PMID36518809
PMCPMC9744611
OpenAlexW4311620397

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.