Evidence map›Paper›PMID 34828379›Full record

ArticleGenes2021

Niyazi Senturk, Gulten Tuncel, Berkcan Dogan, Lamiya Aliyeva, Mehmet Sait Dundar, Sebnem Ozemri Sag, Gamze Mocan, Sehime Gulsun Temel, Munis Dundar, Mahmut Cerkez Ergoren

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genes, 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. Different perspectives on translational genomics in personalized medicineJournal of the Turkish German Gynecological Association · 2022
    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

10 authors.

Niyazi SenturkDepartment of Biomedical Engineering, Faculty of Engineering, Near East University, Nicosia 99138, Cyprus.
Gulten TuncelDESAM Research Institute, Near East University, Nicosia 99138, Cyprus.
Berkcan DoganDepartment of Medical Genetics, Faculty of Medicine, Bursa Uludag University, Bursa 16059, Turkey.ORCID 0000-0001-8061-8131
Lamiya AliyevaDepartment of Medical Genetics, Faculty of Medicine, Bursa Uludag University, Bursa 16059, Turkey.
Mehmet Sait DundarDepartment of Electrical and Computer Engineering, Graduate School of Engineering and Natural Sciences, Abdullah Gul University, Kayseri 38000, Turkey.
Sebnem Ozemri SagDepartment of Medical Genetics, Faculty of Medicine, Bursa Uludag University, Bursa 16059, Turkey.
Gamze MocanDepartment of Medical Pathology, Faculty of Medicine, Near East University, Nicosia 99138, Cyprus.
Sehime Gulsun TemelDepartment of Medical Genetics, Faculty of Medicine, Bursa Uludag University, Bursa 16059, Turkey.ORCID 0000-0002-9802-0880
Munis DundarDepartment of Medical Genetics, Faculty of Medicine, Erciyes University, Kayseri 38000, Turkey.ORCID 0000-0003-0969-4611
Mahmut Cerkez ErgorenDESAM Research Institute, Near East University, Nicosia 99138, Cyprus.ORCID 0000-0001-9593-9325

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence provides modelling on machines by simulating the human brain using learning and decision-making abilities. Early diagnosis is highly effective in reducing mortality in cancer. This study aimed to combine cancer-associated risk factors including genetic variations and design an artificial intelligence system for risk assessment. Data from a total of 268 breast cancer patients have been analysed for 16 different risk factors including genetic variant classifications. In total, 61

Indexed as

Genetic VariationAdolescentAdultAgedArtificial IntelligenceBRCA1 ProteinBRCA2 ProteinBreast NeoplasmsComputational BiologyDatabases, GeneticFemaleFuzzy LogicHumansMiddle AgedNeural Networks, ComputerRetrospective StudiesBRCA1 ProteinBRCA1 protein, humanBRCA2 ProteinBRCA2 protein, humanartificial intelligenceBRCA1BRCA2breast cancertranslational fuzzy logicvariation

Identifiers

PMID34828379
PMCPMC8623958

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.