Evidence map›Paper›PMID 38899014›Full record

ArticleIEEE open journal of engineering in medicine and biology2024

Chronic Wound Image Augmentation and Assessment Using Semi-Supervised Progressive Multi-Granularity EfficientNet.

Ziyang Liu, Emmanuel Agu, Peder Pedersen, Clifford Lindsay, Bengisu Tulu, Diane Strong

Abstract read
In one paragraph

Article in IEEE open journal of engineering in medicine and biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Research Progress on Artificial Intelligence in the Management of Diabetic Foot Ulcers.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026
    Review
  4. Multimodal AI for Home Wound Patient Referral Decisions From Images With Specialist Annotations.IEEE journal of translational engineering in health and medicine · 2025
    Article
  5. Article
  6. 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

6 authors.

Ziyang LiuComputer Science DepartmentWorcester Polytechnic Institute Worcester MA 01609 USA.ORCID https://orcid.org/0000-0001-5419-1250
Emmanuel AguComputer Science DepartmentWorcester Polytechnic Institute Worcester MA 01609 USA.ORCID https://orcid.org/0000-0002-3361-4952
Peder PedersenElectrical and Computer Engineering DepartmentWorcester Polytechnic Institute Worcester MA 01609 USA.ORCID https://orcid.org/0000-0002-7917-7209
Clifford LindsayDepartment of RadiologyUniversity of Massachusetts Medical School Worcester MA 01609 USA.
Bengisu TuluFoisie Business SchoolWorcester Polytechnic Institute Worcester MA 01609 USA.ORCID https://orcid.org/0000-0001-7226-1830
Diane StrongFoisie Business SchoolWorcester Polytechnic Institute Worcester MA 01609 USA.ORCID https://orcid.org/0000-0002-1756-0464

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Chronic woundsdata augmentationdata imbalanceneural networkssmartphone assessment

Identifiers

PMID38899014
PMCPMC11186650

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.