Evidence map›Paper›PMID 36277002›Full record

ArticleComputational and mathematical methods in medicine2022

Computational and Mathematical Methods in Medicine Glioma Brain Tumor Detection and Classification Using Convolutional Neural Network.

S Saravanan, V Vinoth Kumar, Velliangiri Sarveshwaran, Alagiri Indirajithu, D Elangovan, Shaikh Muhammad Allayear

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

16 citing papers in PubMed, 46 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

6 authors at 5 institutions in 2 countries.

S SaravananDepartment of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, India.
V Vinoth KumarDepartment of Computer Science and Engineering, Jain (Deemed to Be University), Bangalore, India.
Velliangiri SarveshwaranDepartment of Computational Intelligence, SRM Institute of Science and Technology, Kattankulathur Campus, Chennai, India.
Alagiri IndirajithuSchool of Information Technology and Engineering, Vellore Institute of Technology, Vellore, 632014 Tamil Nadu, India.
D ElangovanDepartment of Computer Science and Engineering, Panimalar Engineering College, Chennai, Tamil Nadu, India.
Shaikh Muhammad AllayearDepartment of Multimedia and Creative Technology, Daffodil International University, Daffodil Smart City, Khagan, Ashulia, Dhaka, Bangladesh.ORCID https://orcid.org/0000-0003-0567-7865
Daffodil International University · BDJain University · INSRM Institute of Science and Technology · INVellore Institute of Technology University · INVel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The classification of the brain tumor image is playing a vital role in the medical image domain, and it directly assists the clinicians to understand the severity and to take an appropriate solution. The magnetic resonance imaging tool is used to analyze the brain tissues and to examine the different portion of brain circumstance. We propose the convolutional neural network database learning along with neighboring network limitation (CD

Indexed as

Brain NeoplasmsGliomaBrainHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingNeural Networks, Computer

Identifiers

PMID36277002
PMCPMC9586767
OpenAlexW4306249295

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.