Evidence map›Paper›PMID 33263808›Full record

ReviewDer Pathologe2020

[Technical, operational, and regulatory considerations for the adoption of digital and computational pathology].

Markus D Herrmann, Jochen K Lennerz

Abstract readReview
PubMed Publisher
In one paragraph

Review in Der Pathologe, 2020. 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, top 84% of its field
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, 2 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Markus D HerrmannDepartment of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. mdherrmann@mgh.harvard.edu.
Jochen K LennerzDepartment of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Massachusetts General Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInnovative information technologies open new possibilities for diagnostics and promise to improve patient care. However, the integration of data- and computing-intensive procedures into diagnostic workflows also poses risks and considerable challenges for pathologists.

objectivesConsidering technical, operational, and regulatory aspects, we present a holistic and systematic approach for the adoption of digital and computational pathology. MATERIAL AND

methodsWe discuss challenges for the implementation of computational diagnostic procedures and analyze regulatory frameworks for risk-based assessment and monitoring of software as an in vitro diagnostic device. Applying regulatory science, we develop an approach to streamline adoption of digital workflows in pathology.

resultsData- and computing-intensive workflows in digital pathology are complex and underscore the need for computational and regulatory science as a central part of pathological diagnostics. To promote the adoption of computational diagnostics, we have founded an interdisciplinary initiative (the Alliance) that focuses on regulatory research in the field of digital pathology and works closely with a number of expert and interest groups on the precompetitive development of standards for computational workflows. DISCUSSION: The inclusion of different stakeholder groups and the coordination of technical, operational, and regulatory aspects is necessary to maintain the balance between progress and safety in diagnostics and to make innovations quickly and safely available for patient care.

Indexed as

PathologistsSoftwareHumansWorkflowArtificial intelligenceIn vitro diagnosticsMachine learningQuality assuranceRegulatory science

Identifiers

PMID33263808
OpenAlexW3109024354

What OpenQuestion holds

Textmetadata
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.