Evidence map›Paper›PMID 40428264›Full record

ArticleDiagnostics (Basel, Switzerland)2025

Comparative Study of Cell Nuclei Segmentation Based on Computational and Handcrafted Features Using Machine Learning Algorithms.

Rashadul Islam Sumon, Md Ariful Islam Mozumdar, Salma Akter, Shah Muhammad Imtiyaj Uddin, Mohammad Hassan Ali Al-Onaizan, Reem Ibrahim Alkanhel, Mohammed Saleh Ali Muthanna

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

7 authors.

Rashadul Islam SumonInstitute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea.ORCID 0000-0003-3610-2562
Md Ariful Islam MozumdarInstitute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea.ORCID 0000-0001-6095-0700
Salma AkterInstitute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea.
Shah Muhammad Imtiyaj UddinInstitute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea.ORCID 0009-0000-5484-8857
Mohammad Hassan Ali Al-OnaizanDepartment of Intelligent Systems Engineering, Faculty of Engineering and Design, Middle East University, Amman 11831, Jordan.ORCID 0009-0008-5321-077X
Reem Ibrahim AlkanhelDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.ORCID 0000-0001-6395-4723
Mohammed Saleh Ali MuthannaDepartment of International Business Management, Tashkent State University of Economics, Tashkent 100066, Uzbekistan.

Funding

This paper is supported by Princess Nourah bint Abdulrahman University Researchers Support-ing Project number (PNURSP2025R323), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia PNURSP2025R323
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

cell nucleideep learningfeature extractionmachine learningprostate cancersegmentation

Identifiers

PMID40428264
PMCPMC12110490

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.