Evidence map›Paper›PMID 40599690›Full record

ReviewJournal of pathology informatics2025

Advancing open-source visual analytics in digital pathology: A systematic review of tools, trends, and clinical applications.

Zahoor Ahmad, Mahmood Alzubaidi, Khaled Al-Thelaya, Corrado Calí, Sabri Boughorbel, Jens Schneider, Marco Agus

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of pathology informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Detection ofJournal of imaging · 2025
    Article
  5. 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

7 authors.

Zahoor AhmadCollege of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, 34110 Doha, Qatar.
Mahmood AlzubaidiCollege of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, 34110 Doha, Qatar.
Khaled Al-ThelayaCollege of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, 34110 Doha, Qatar.
Corrado CalíNeuroscience Institute Cavalieri Ottolenghi, University of Turin, Orbassano, Italy.
Sabri BoughorbelQatar Computing Research Institute, Hamad Bin Khalifa University, Qatar Foundation, 34110 Doha, Qatar.
Jens SchneiderCollege of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, 34110 Doha, Qatar.
Marco AgusCollege of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, 34110 Doha, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histopathology is critical for disease diagnosis, and digital pathology has transformed traditional workflows by digitizing slides, enabling remote consultations, and enhancing analysis through computational methods. In this systematic review, we evaluated open-source visual analytics abilities in digital pathology by screening 254 studies and including 52 that met predefined criteria. Our analysis reveals that these solutions-comprising abilities (

Indexed as

Cancer researchClinical implementationComputational pathologyDigital pathologyHistopathologyImage analysisMachine learning in pathologyOpen-sourceVisual analyticsWhole slide imaging

Identifiers

PMID40599690
PMCPMC12210317

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.