Evidence map›Paper›PMID 36568775›Full record

ArticleFrontiers in public health2022

Practice toward standardized performance testing of computer-aided detection algorithms for pulmonary nodule.

Hao Wang, Na Tang, Chao Zhang, Ye Hao, Xiangfeng Meng, Jiage Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. 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
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.

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

6 authors.

Hao WangDivision of Active Medical Device and Medical Optics, Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, China.
Na TangSchool of Bioengineering, Chongqing University, Chongqing, China.
Chao ZhangDivision of Active Medical Device and Medical Optics, Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, China.
Ye HaoDivision of Active Medical Device and Medical Optics, Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, China.
Xiangfeng MengDivision of Active Medical Device and Medical Optics, Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, China.
Jiage LiDivision of Active Medical Device and Medical Optics, Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed at implementing practice to build a standardized protocol to test the performance of computer-aided detection (CAD) algorithms for pulmonary nodules. A test dataset was established according to a standardized procedure, including data collection, curation and annotation. Six types of pulmonary nodules were manually annotated as reference standard. Three specific rules to match algorithm output with reference standard were applied and compared. These rules included: (1) "center hit" [whether the center of algorithm highlighted region of interest (ROI) hit the ROI of reference standard]; (2) "center distance" (whether the distance between algorithm highlighted ROI center and reference standard center was below a certain threshold); (3) "area overlap" (whether the overlap between algorithm highlighted ROI and reference standard was above a certain threshold). Performance metrics were calculated and the results were compared among ten algorithms under test (AUTs). The test set currently consisted of CT sequences from 593 patients. Under "center hit" rule, the average recall rate, average precision, and average F

Indexed as

Lung NeoplasmsAlgorithmsComputersHumansRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray Computedalgorithm testingcomputer-aided detection (CAD)data curationpulmonary noduletest set

Identifiers

PMID36568775
PMCPMC9768365

What OpenQuestion holds

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Registered trials

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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.