Evidence map›Paper›PMID 30167342›Full record

ArticleJournal of pathology informatics2018

Will Digital Pathology be as Disruptive as Genomics?

Steven N Hart

Open access · goldAbstract read
In one paragraph

Article in Journal of pathology informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Review
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

1 author at 1 institution in 1 country.

Steven N HartDepartment of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
Mayo Clinic in Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital pathology is the science of performing traditional pathological assessment in a digital environment. A digital transition is long overdue since histochemical analysis such as hematoxylin and eosin staining has remained unchanged in over 100 years. Importantly, the digitization of whole slide images further lends itself to advances in computational pathology and artificial intelligence to transform qualitative assessment into quantitative assessment. The impact of this transition from a computational infrastructure perspective is reminiscent of a similar transition in the field of genomics. In this article, I describe some of the similarities between genomics and digital pathology as well as highlight some key lessons learned to prevent the same mistakes and delays that slowed the genomics revolution.

Indexed as

bioinformaticsdigital pathologyGenomics

Identifiers

PMID30167342
PMCPMC6106127
OpenAlexW2884072513

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.