Evidence map›Paper›PMID 32385375›Full record

ArticleScientific reports2020

Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on

MuthuSubash Kavitha, Chang-Hee Lee, KattakkaliSubhashdas Shibudas, Takio Kurita, Byeong-Cheol Ahn

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. KSNM60 in Nuclear Endocrinology: from the Beginning to the Future.Nuclear medicine and molecular imaging · 2022
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

MuthuSubash Kavitha *Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan.ORCID http://orcid.org/0000-0002-1676-561X
Chang-Hee Lee *Department of Nuclear Medicine, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, South Korea.
KattakkaliSubhashdas ShibudasSchool of Electronics Engineering, Kyungpook National University, Daegu, South Korea.
Takio KuritaGraduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan. tkurita@hiroshima-u.ac.jp.ORCID http://orcid.org/0000-0003-3982-6750
Byeong-Cheol AhnDepartment of Nuclear Medicine, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, South Korea. abc2000@knu.ac.kr.
Hiroshima University · JPKyungpook National University Hospital · KRKyungpook National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on

Indexed as

Ablation TechniquesDeep LearningIodine RadioisotopesWhole Body ImagingAutomationHumansImage Processing, Computer-AssistedLymphatic MetastasisRetrospective StudiesSingle Photon Emission Computed Tomography Computed TomographyThyroid NeoplasmsIodine-131Iodine Radioisotopes

Identifiers

PMID32385375
PMCPMC7211007
OpenAlexW3021954209

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.