Evidence map›Paper›PMID 34552975›Full record

ArticleFrontiers in veterinary science2021

Deep-Learning-Based Automatic Segmentation of Head and Neck Organs for Radiation Therapy in Dogs.

Jeongsu Park, Byoungsu Choi, Jaeeun Ko, Jaehee Chun, Inkyung Park, Juyoung Lee, Jayon Kim, Jaehwan Kim, Kidong Eom, Jin Sung Kim

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2021. 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.

  1. Article
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  8. Employing deep convolutional neural networks for segmenting the medial retropharyngeal lymph nodes in CT studies of dogs.Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association · 2022
    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

10 authors.

Jeongsu ParkDepartment of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, South Korea.
Byoungsu ChoiDepartment of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
Jaeeun KoDepartment of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, South Korea.
Jaehee ChunDepartment of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
Inkyung ParkDepartment of Integrative Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
Juyoung LeeDepartment of Integrative Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
Jayon KimDepartment of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, South Korea.
Jaehwan KimDepartment of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, South Korea.
Kidong EomDepartment of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, South Korea.
Jin Sung KimDepartment of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial intelligencedeep-learning-based automatic segmentationdog head and neckhead and neck cancerradiation therapy

Identifiers

PMID34552975
PMCPMC8450455

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.