S

Uttam Waghmode, Ashwini Naik, Jyoti Deone, Somdotta Roy Choudhury, Dhanashri Dhawale, Digambar Puri, Surendra Solanki

Abstract read

In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Uttam WaghmodeRamrao Adik Institute of Technology, Navi Mumbai, India.

Ashwini NaikRamrao Adik Institute of Technology, Navi Mumbai, India.

Jyoti DeoneRamrao Adik Institute of Technology, Navi Mumbai, India.

Somdotta Roy ChoudhuryRamrao Adik Institute of Technology, Navi Mumbai, India.

Dhanashri DhawaleLokmanya Tilak College of Engineering, Koparkhairane, Navi Mumbai, India.

Digambar PuriDepartment of Information Technology, Vidhyalankar Institute of Technology, Wadala, Mumbai, India.

Surendra SolankiDepartment of Artificial Intelligence and Machine Learning, Manipal University Jaipur, Jaipur, 303007, Rajasthan, India. surendra.solanki@jaipur.manipal.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Globally, the main factor that contributes to increasing the mortality rate among people is the development of abnormal cells in the brain, which leads to a Brain Tumor (BT). Therefore, the classification of BT is essential to prevent the increasing death rate by diagnosing the tumor based on its type. In order to classify the types of BT, several models are introduced, but they possess numerous drawbacks, including poor accuracy, higher time consumption, computational complexities, overfitting, and so forth. Hence, the Standalone Self-Attention based Repeated Convolutional Network (

Indexed as

Brain NeoplasmsDeep LearningMagnetic Resonance ImagingConvolutional Neural NetworksHumans

Identifiers

PMID42034851

DOI10.1038/s41598-026-46010-1

PMCPMC13279802

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.