Evidence map›Paper›PMID 37928169›Full record

ArticleFrontiers in bioinformatics2023

3D multiplexed tissue imaging reconstruction and optimized region of interest (ROI) selection through deep learning model of channels embedding.

Erik Burlingame, Luke Ternes, Jia-Ren Lin, Yu-An Chen, Eun Na Kim, Joe W Gray, Young Hwan Chang

Abstract read
In one paragraph

Article in Frontiers in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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  4. Review
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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.

Erik Burlingame *Department of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.
Luke Ternes *Department of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.
Jia-Ren LinLudwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, United States.
Yu-An ChenLudwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, United States.
Eun Na KimDepartment of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.
Joe W GrayDepartment of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.
Young Hwan ChangDepartment of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, United States.

Funding

Understanding the Impact of Microscale and Nanoscale Heterogeneity and ResistanceU54CA209988 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI DEMIR, EMEK, HEISER, LAURA MADELINE · 2017 to 2021
$10.3M
Omic and Multidimensional Spatial Atlas of Metastatic Breast CancerU2CCA233280 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI DEMIR, EMEK, MILLS, GORDON B. · 2018 to 2023
$9.7M
Integrative single cell analyses of inflammation-derived circulating hybrid cells to identify aggressive diseaseR01CA253860 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI CHANG, YOUNG HWAN, WONG, MELISSA H. · 2021 to 2025
$3.0M
NCI NIH HHS R01 CA253860NCI NIH HHS U2C CA233280NCI NIH HHS U54 CA209988
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

3D multiplex tissue imaging3D virtual CyCIFchannels embeddingmultimodal integrationoptimized region of interest selection

Identifiers

PMID37928169
PMCPMC10620917

What OpenQuestion holds

Textmetadata
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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.