Evidence map›Paper›PMID 31903408›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2020

Is there a safety-net effect with computer-aided detection?

Ethan Du-Crow, Susan M Astley, Johan Hulleman

Open access · greenAbstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. The optimal use of computer aided detection to find low prevalence cancers.Cognitive research: principles and implications · 2022
    Article
  3. 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

3 authors at 1 institution in 1 country.

Ethan Du-CrowDivision of Informatics, Imaging and Data Sciences, University of Manchester, Faculty of Biology, Medicine and Health, Manchester, United Kingdom.ORCID https://orcid.org/0000-0003-1958-6008
Susan M AstleyDivision of Informatics, Imaging and Data Sciences, University of Manchester, Faculty of Biology, Medicine and Health, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-2989-2765
Johan HullemanDivision of Neuroscience and Experimental Psychology, University of Manchester, Faculty of Biology, Medicine and Health, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-6900-5190
University of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computer-aided detection (CAD) systems are used to aid readers interpreting screening mammograms. An expert reader searches the image initially unaided and then once again with the aid of CAD, which prompts automatically detected suspicious regions. This could lead to a "safety-net" effect, where the initial unaided search of the image is adversely affected by the fact that it is preliminary to an additional search with CAD and may, therefore, be less thorough. To investigate the existence of such an effect, we created a visual search experiment for nonexpert observers mirroring breast screening with CAD. Each observer searched 100 images for microcalcification clusters within synthetic images in both prompted (CAD) and unprompted (no-CAD) conditions. Fifty-two participants were recruited for the study, 48 of whom had their eye movements tracked in real-time; the other 4 participants could not be accurately calibrated, so only behavioral data were collected. In the CAD condition, before prompts were displayed, image coverage was significantly lower than coverage in the no-CAD condition (

Indexed as

breast cancercomputer-aided detectioneye-trackingimage perceptionmammographyvisual search

Identifiers

PMID31903408
PMCPMC6931663
OpenAlexW2997829591

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.