Evidence map›Paper›PMID 41971910›Full record

ArticleJournal of pathology informatics2026

Perceptions of digital pathology among healthcare workers in pathology.

Aditi Tayal, Meghan E Kapp, Sylvia L Asa

Abstract read
In one paragraph

Article 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

3 authors.

Aditi TayalUniversity Hospitals Cleveland Medical Center, Case Western Reserve University, School of Medicine, Cleveland, OH, USA.
Meghan E KappUniversity Hospitals Cleveland Medical Center, Case Western Reserve University, School of Medicine, Cleveland, OH, USA.
Sylvia L AsaUniversity Hospitals Cleveland Medical Center, Case Western Reserve University, School of Medicine, Cleveland, OH, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of informatics into pathology is rapidly transforming the field, with the potential to enhance diagnostic accuracy, streamline workflows, and improve patient outcomes. Digital pathology, artificial intelligence (AI), and machine learning are among the innovations revolutionizing traditional practices by enabling the digitization of tissue samples, the automation of data analysis, and the incorporation of large datasets into diagnostic processes. While these advancements hold great promise, they have also generated mixed reactions among healthcare professionals, particularly in pathology, where the balance between human expertise and technology is critical. To better understand the perceptions of informatics in pathology, a cross-sectional survey was conducted among healthcare workers within the field. The survey aimed to assess attitudes toward the adoption of informatics, with specific focus on its perceived benefits and challenges. This study seeks to provide insights into how these new technologies are being received by those at the forefront of pathology, exploring both the enthusiasm and apprehension surrounding the growing role of informatics in the discipline.

Indexed as

Artificial intelligenceDigital pathologyGlass slidePathologist

Identifiers

PMID41971910
PMCPMC13068662

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.