Evidence map›Paper›PMID 35626198›Full record

ReviewDiagnostics (Basel, Switzerland)2022

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective.

Rachel N Flach, Nina L Fransen, Andreas F P Sonnen, Tri Q Nguyen, Gerben E Breimer, Mitko Veta, Nikolas Stathonikos, Carmen van Dooijeweert, Paul J van Diest

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Deep Learning Image Processing Models in Dermatopathology.Diagnostics (Basel, Switzerland) · 2025
    Review
  4. Article
  5. Article
  6. 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

9 authors.

Rachel N FlachDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.ORCID 0000-0002-4448-2895
Nina L FransenDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.ORCID 0000-0003-0958-7162
Andreas F P SonnenDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.
Tri Q NguyenDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.ORCID 0000-0001-6475-0706
Gerben E BreimerDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.ORCID 0000-0003-0365-3667
Mitko VetaDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.
Nikolas StathonikosDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.
Carmen van DooijeweertDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.ORCID 0000-0001-8030-4335
Paul J van DiestDepartment of Pathology, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Building on a growing number of pathology labs having a full digital infrastructure for pathology diagnostics, there is a growing interest in implementing artificial intelligence (AI) algorithms for diagnostic purposes. This article provides an overview of the current status of the digital pathology infrastructure at the University Medical Center Utrecht and our roadmap for implementing AI algorithms in the next few years.

Indexed as

artificial intelligencedigital pathologyimplementationmachine learningroadmap

Identifiers

PMID35626198
PMCPMC9140005

What OpenQuestion 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 OpenQuestion graph.