Enhancing Early Detection of Diabetic Foot Ulcers Using Deep Neural Networks.

A Sharaf Eldin, Asmaa S Ahmoud, Hanaa M Hamza, Hanin Ardah

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.

AI-Enhanced System for Diabetic Foot Ulcer Localization and Classification Using Multi-Scale Neural CNN Model.Health science reports · 2026
Article
Advances in the application of artificial intelligence-driven multi-modal imaging technologies in the comprehensive diagnosis and treatment of diabetic foot ulcers.Reviews in endocrine & metabolic disorders · 2026
Review
AI-Based Models for Diabetic Foot Ulcer Assessment: Scoping Review.JMIR diabetes · 2026
Review
Advances in Image-Based Diagnosis of Diabetic Foot Ulcers Using Deep Learning and Machine Learning: A Systematic Review.Biomedicines · 2025
Review

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

4 authors.

A Sharaf EldinDepartment of Information and Decision Support Systems, Faculty of Information Technology and Computer Science, Sinai University, Arish 16020, Egypt.ORCID 0000-0003-2245-8349

Asmaa S AhmoudDepartment of Information Technology, Faculty of Information Technology and Computer Science, Sinai University, Arish 16020, Egypt.ORCID 0009-0005-9543-8498

Hanaa M HamzaDepartment of Information Technology, Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt.ORCID 0000-0003-1008-2612

Hanin ArdahDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.ORCID 0009-0007-7123-9616

Funding

This research was funded by Princess Nourah bint Abdulrahman University. PURSP2025R893

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

deep learning (DL)deep neural network (DNN)diabetic footdiabetic foot ulcers (DFUs)plantar thermogramsthermal images

Identifiers

PMID40870850

DOI10.3390/diagnostics15161996

PMCPMC12385524

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.