Evidence map›Paper›PMID 42761211›Full record

ReviewJournal of pathology informatics2026

Whole-slide imaging in hematopathology: Current state, challenges and future opportunities.

Reyhaneh Norouziani, Shay Yakobov, Hamid R Tizhoosh, Clinton J V Campbell

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of pathology informatics, 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

4 authors.

Reyhaneh NorouzianiFaculty of Health Sciences, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada.
Shay YakobovRady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, 727 McDermot Avenue, University of Manitoba (Bannatyne Campus), Winnipeg, MB R3E 3P5, Canada.
Hamid R TizhooshKIMIA Lab, Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN 55901, USA.
Clinton J V CampbellFaculty of Health Sciences, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-slide imaging (WSI) is gradually being adopted for primary diagnosis in many pathology subspecialties. The benefits of WSI for the pathology workflow are numerous and include the use of artificial intelligence (AI) tools to support WSI analysis. However, digitization of hematopathology workflows has remained a challenge, in part due to the complexity of the hematopathology workflow and the unique characteristics of blood and bone marrow smears. Although AI applications to support hematopathology tasks, such as nucleated differential counts, are well-described, general implementation of these tools has been limited due to the lack of widely available WSIs. Consequently, there is an unmet need for new and innovative solutions to WSI in hematopathology. This review focuses on WSI of hematopathology cytological specimens, particularly, peripheral blood and bone marrow smears, and summarizes unique challenges and AI solutions to support WSI analysis in this area. We also discuss future opportunities for hematopathologist-driven innovation in AI and WSI in hematopathology.

Indexed as

Artificial intelligenceDigital pathologyHematopathologyWhole-slide imaging

Identifiers

PMID42761211
PMCPMC13586566

What OpenQuestion holds

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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.