Evidence map›Paper›PMID 23927365›Full record

ArticleMedical physics2013

Evaluation of computer-aided detection and diagnosis systems.

Nicholas Petrick, Berkman Sahiner, Samuel G Armato, Alberto Bert, Loredana Correale, Silvia Delsanto, Matthew T Freedman, David Fryd, David Gur, Lubomir Hadjiiski and 12 more

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in Medical physics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
7.0field-weighted citation impact, top 3% 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

52 citing papers in PubMed, 2 syntheses or guidelines pooled it, 139 citations in OpenAlex.

  1. Pooled it
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  4. Article
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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

22 authors at 13 institutions in 3 countries.

Nicholas PetrickCenter for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993, USA.
Berkman Sahiner
Samuel G Armato
Alberto Bert
Loredana Correale
Silvia Delsanto
Matthew T Freedman
David Fryd
David Gur
Lubomir Hadjiiski
Zhimin Huo
Yulei Jiang
Lia Morra
Sophie Paquerault
Vikas Raykar
Frank Samuelson
Ronald M Summers
Georgia Tourassi
Hiroyuki Yoshida
Bin Zheng
Chuan Zhou
Heang-Ping Chan
Torino e-district · ITUniversity of Michigan–Ann Arbor · USCenter for Devices and Radiological Health · USUniversity of Chicago · USCarestream (United States) · USGeorgetown University Medical Center · USHarvard University · USIBM Research - India · INNational Institutes of Health Clinical Center · USOak Ridge National Laboratory · USUnited States Food and Drug Administration · USUniversity of Oklahoma · USUniversity of Pittsburgh · US

Funding

Computer Aided Detection for Radiologic ImagesZIACL040004 · CLC · CLINICAL CENTER · PI SUMMERS, RONALD M. · 2009 to 2025
$0k
Intramural NIH HHS
6 · The paper itself

Abstract

Computer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. Computer-aided detection systems mark regions of an image that may reveal specific abnormalities and are used to alert clinicians to these regions during image interpretation. Computer-aided diagnosis systems provide an assessment of a disease using image-based information alone or in combination with other relevant diagnostic data and are used by clinicians as a decision support in developing their diagnoses. While CAD systems are commercially available, standardized approaches for evaluating and reporting their performance have not yet been fully formalized in the literature or in a standardization effort. This deficiency has led to difficulty in the comparison of CAD devices and in understanding how the reported performance might translate into clinical practice. To address these important issues, the American Association of Physicists in Medicine (AAPM) formed the Computer Aided Detection in Diagnostic Imaging Subcommittee (CADSC), in part, to develop recommendations on approaches for assessing CAD system performance. The purpose of this paper is to convey the opinions of the AAPM CADSC members and to stimulate the development of consensus approaches and "best practices" for evaluating CAD systems. Both the assessment of a standalone CAD system and the evaluation of the impact of CAD on end-users are discussed. It is hoped that awareness of these important evaluation elements and the CADSC recommendations will lead to further development of structured guidelines for CAD performance assessment. Proper assessment of CAD system performance is expected to increase the understanding of a CAD system's effectiveness and limitations, which is expected to stimulate further research and development efforts on CAD technologies, reduce problems due to improper use, and eventually improve the utility and efficacy of CAD in clinical practice.

Indexed as

ConsensusDiagnosis, Computer-AssistedHumansReference StandardsRetrospective StudiesROC CurveSocieties, Medical

Identifiers

PMID23927365
PMCPMC4108682
OpenAlexW2065524237

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.