Evidence map›Paper›PMID 42463523›Full record

ArticleScientific data2026

The PAR dataset: Prostate biopsy whole slide images from an underrepresented Middle Eastern population.

Peshawa J Muhammad Ali, Navin Vincent, Saman S Abdulla, Han N Mohammed Fadhl, Anders Blilie, Kelvin Szolnoky, Julia Anna Mielcarz, Xiaoyi Ji, Kimmo Kartasalo, Abdulbasit K Al-Talabani and 1 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Peshawa J Muhammad Ali *Department of Software Engineering, Faculty of Engineering, Koya University, 44023, Kurdistan Region, Koya, Iraq.
Navin Vincent *Department of Medical Epidemiology and Biostatistics, SciLifeLab, Karolinska Institutet, Stockholm, Sweden.
Saman S AbdullaCollege of Dentistry, Hawler Medical University, Erbil, Kurdistan Region, Iraq.
Han N Mohammed FadhlCollege of Dentistry, University of Sulaimani, Sulaymaniyah, Kurdistan Region, Iraq.
Anders BlilieDepartment of Pathology, Stavanger University Hospital, Stavanger, Norway.
Kelvin SzolnokyDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Julia Anna MielcarzDepartment of Medical Epidemiology and Biostatistics, SciLifeLab, Karolinska Institutet, Stockholm, Sweden.
Xiaoyi JiDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Kimmo KartasaloDepartment of Medical Epidemiology and Biostatistics, SciLifeLab, Karolinska Institutet, Stockholm, Sweden.
Abdulbasit K Al-TalabaniDepartment of Software Engineering, Faculty of Engineering, Koya University, 44023, Kurdistan Region, Koya, Iraq.
Nita MulliqiDepartment of Medical Epidemiology and Biostatistics, SciLifeLab, Karolinska Institutet, Stockholm, Sweden. nita.mulliqi@ki.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly used in digital pathology. Publicly available histopathology datasets remain scarce, and those that do exist predominantly represent Western populations. Consequently, the generalizability of AI models to populations from less digitized regions, such as the Middle East, is largely unknown. This motivates the public release of our dataset to support the development and validation of pathology AI models across globally diverse populations. We present 1,017 whole slide images by digitizing 339 glass slides of prostate core needle biopsies from a consecutive series of 185 patients collected in Erbil, Iraq. Each glass slide was scanned by three different whole-slide scanners. The dataset also includes the corresponding Gleason Scores and the International Society of Urological Pathology grades assigned independently by three pathologists. All slides were de-identified and are provided in their native formats without further conversion. The dataset enables grading concordance analyses, color normalization, and cross-scanner robustness evaluations. The dataset is publicly available through the BioImage Archive and released under the CC BY 4.0 license.

Indexed as

ProstateProstatic NeoplasmsArtificial IntelligenceBiopsy, Large-Core NeedleHumansIraqMaleMiddle EastNeoplasm Grading

Identifiers

PMID42463523
PMCPMC13377206

What Socratic 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 Socratic graph.