Evidence map›Paper›PMID 38744304›Full record

ArticlePhysics in medicine and biology2024

Human-like intelligent automatic treatment planning of head and neck cancer radiation therapy.

Yin Gao, Yang Kyun Park, Xun Jia

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Enhancing IMRT/VMAT Competencies in LMICs globally within radiation physicists through remote training.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025
    Article
  11. Article
  12. Article
  13. Review
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

3 authors.

Yin GaoDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States of America.ORCID 0000-0002-6998-2087
Yang Kyun ParkDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States of America.ORCID 0000-0002-3784-2653
Xun JiaDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, United States of America.ORCID 0000-0001-6159-2909

Funding

Human-like automated radiotherapy treatment planning via imitation learningR01CA254377 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI JIA, XUN, JIANG, STEVE BIN · 2021 to 2025
$2.9M
Intelligent treatment planning for cancer radiotherapyR01CA237269 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI JIA, XUN, JIANG, STEVE BIN · 2019 to 2023
$2.5M
NCI NIH HHS R01 CA237269NCI NIH HHS R01 CA254377
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

AutomationHead and Neck NeoplasmsRadiotherapy Planning, Computer-AssistedArtificial IntelligenceHumansRadiotherapy Dosageautomatic treatment planningdeep reinforcement learningH&N cancerradiation therapy

Identifiers

PMID38744304
PMCPMC11148880

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.