ReviewDigital health
Digital pathology: Barriers to transitioning to the digital age.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Artificial intelligence in prostate biopsy: diagnostic applications, risk stratification, and precision oncology.Frontiers in oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Digital pathology (DP) entails converting physical histologic data into a digital format, ultimately enhancing data transmission, archival, and retrieval. Moreover, digitization serves as an essential prerequisite for utilizing artificial intelligence programs in histologic image analysis. Clinical use of DP has had limited uptake despite its transformative potential and numerous proposed benefits. This paper explores the commonly cited workflow, regulatory, and financial barriers currently hindering DP implementation based on the published experiences of early adopters. It provides an overview of topics including relevant regulatory bodies and guidelines, cost-to-benefit analysis, data management, and the role of artificial intelligence within DP.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.