Evidence map›Paper›PMID 41897581›Full record

ArticleDiagnostics (Basel, Switzerland)2026

A Hybrid Multimodal Cancer Diagnostic Framework Integrating Deep Learning of Histopathology and Whispering Gallery Mode Optical Sensors.

Shereen Afifi, Amir R Ali, Nada Haytham Abdelbasset, Youssef Poulis, Yasmin Yousry, Mohamed Zinal, Hatem S Abdullah, Miral Y Selim, Mohamed Hamed

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diagnostics (Basel, Switzerland), 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

9 authors.

Shereen AfifiComputer Science and Engineering Department, Faculty of Media Engineering and Technology (MET), German University in Cairo (GUC), New Cairo 11835, Egypt.ORCID 0000-0003-2383-4721
Amir R AliMechatronics Engineering Department, Faculty of Engineering and Materials Science (EMS), German University in Cairo (GUC), New Cairo 11835, Egypt.ORCID 0000-0001-9159-0277
Nada Haytham AbdelbassetComputer Science and Engineering Department, Faculty of Media Engineering and Technology (MET), German University in Cairo (GUC), New Cairo 11835, Egypt.
Youssef PoulisComputer Science and Engineering Department, Faculty of Media Engineering and Technology (MET), German University in Cairo (GUC), New Cairo 11835, Egypt.
Yasmin YousryProduct Design, Faculty of Applied Sciences and Arts (FASA), German University in Cairo (GUC), New Cairo 11835, Egypt.ORCID 0009-0005-2478-9936
Mohamed ZinalMechatronics Engineering Department, Faculty of Engineering and Materials Science (EMS), German University in Cairo (GUC), New Cairo 11835, Egypt.
Hatem S AbdullahMechatronics Engineering Department, Faculty of Engineering and Materials Science (EMS), German University in Cairo (GUC), New Cairo 11835, Egypt.ORCID 0009-0005-9448-5698
Miral Y SelimMechatronics Engineering Department, Faculty of Engineering and Materials Science (EMS), German University in Cairo (GUC), New Cairo 11835, Egypt.ORCID 0009-0006-9975-0865
Mohamed HamedComputer Science and Engineering Department, Faculty of Media Engineering and Technology (MET), German University in Cairo (GUC), New Cairo 11835, Egypt.ORCID 0000-0002-9102-8839

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

cancer detectiondata augmentationDCGANdeep learningEfficientNethistopathologyInceptionV3multi-class classificationvision transformerWGM optical sensors

Identifiers

PMID41897581
PMCPMC13024953

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.