ReviewJournal of pathology informatics2026
Entity-aware pathology workflow informatics: Structured evidence mapping and a reference architecture for governed orchestration.
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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To map evidence relevant to representing and governing pathology workflows spanning cases, specimens, blocks, slides, scans, and reports, and to derive a reference architecture. Methods: We performed structured evidence mapping with purposive horizon scanning. Searches of Scopus, PubMed, and IEEE Xplore yielded 74 primary database records; Google Scholar and citation tracking contributed 24 supplementary records. Each record contributed one tuple across data acquisition, control-flow reconfiguration, execution autonomy, and validation environment (D1-D4), an author-developed operational taxonomy. Unretained historical search details are reported as a reproducibility constraint, not reconstructed as original methods. Results: The 98-record evidence base spans 1993-2026. Within the 74-record primary corpus, 47 records had dashboard-level execution; validation was split between real-world deployment (26) and conceptual evidence (25). Under study-defined filters, 8/74 records met all 4 minimum capability conditions, 2/74 also showed closed-loop physical actuation, and 1/74 combined full autonomy with real-world deployment. These study-defined filters derive from the original single-reviewer D1-D4 coding. An independent blinded 50-record verification yielded 81.6% inclusion agreement (κ = 0.627) and 80.0% exact D1-D4 field agreement, but did not constitute full-corpus independent reproduction. Supplementary records informed emerging automation requirements. The mapped gaps informed an architecture comprising semantic perception, entity-aware process state, bounded orchestration, pre-action command governance, governed actuation, and conditional local execution support; a safety-and-constraints sandbox is one candidate realization of the governance function. Conclusion: The architecture is an evidence-derived design target, not a deployed or validated system. Evaluation should test event provenance, case-to-slide relationships, robustness to missing or shifted inputs, command constraints, human override, and staged operational performance before autonomy claims.
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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.