Evidence map›Paper›PMID 32118093›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2020

Constructing a tissue-specific texture prior by machine learning from previous full-dose scan for Bayesian reconstruction of current ultralow-dose CT images.

Yongfeng Gao, Jiaxing Tan, Yongyi Shi, Siming Lu, Amit Gupta, Haifang Li, Zhengrong Liang

Abstract 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Artificial Intelligence in Radiation Therapy.IEEE transactions on radiation and plasma medical sciences · 2022
    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

7 authors.

Yongfeng GaoState University of New York, Department of Radiology, Stony Brook, New York, United States.ORCID https://orcid.org/0000-0001-6169-3478
Jiaxing TanState University of New York, Department of Radiology, Stony Brook, New York, United States.
Yongyi ShiState University of New York, Department of Radiology, Stony Brook, New York, United States.
Siming LuState University of New York, Department of Radiology, Stony Brook, New York, United States.
Amit GuptaState University of New York, Department of Radiology, Stony Brook, New York, United States.
Haifang LiState University of New York, Department of Radiology, Stony Brook, New York, United States.
Zhengrong LiangState University of New York, Department of Radiology, Stony Brook, New York, United States.ORCID https://orcid.org/0000-0002-0720-8598

Funding

Advancing Virtual Colonoscopy for Early Cancer ScreeningR01CA206171 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI LIANG, JEROME Z · 2016 to 2020
$2.0M
Screening Lung Cancer by Ultra Low-Dose Computed TomographyR01CA143111 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI LIANG, JEROME Z · 2010 to 2014
$1.6M
NCI NIH HHS R01 CA143111NCI NIH HHS R01 CA206171
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

convolutional neural network tissue-specific texture priormachine learningprelog shift Poisson model

Identifiers

PMID32118093
PMCPMC7040436

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.