Evidence map›Paper›PMID 41308315›Full record

ArticlePhysics in medicine and biology2025

New insights into automatic treatment planning for cancer radiotherapy using explainable artificial intelligence.

Md Mainul Abrar, Xun Jia, Yujie Chi

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Md Mainul AbrarDepartment of Physics, The University of Texas at Arlington, Arlington, TX, United States of America.ORCID 0009-0009-4737-3254
Xun JiaDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, United States of America.ORCID 0000-0001-6159-2909
Yujie ChiDepartment of Physics, The University of Texas at Arlington, Arlington, TX, United States of America.ORCID 0000-0002-1828-3251

Funding

Next generation small animal radiation research platformR37CA214639 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI JIA, XUN · 2018 to 2024
$3.8M
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 CA254377NCI NIH HHS R37 CA214639
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Artificial IntelligenceProstatic NeoplasmsRadiotherapy Planning, Computer-AssistedAutomationHumansMaleRadiotherapy DosageRadiotherapy, Intensity-Modulatedactor critic with experience replayautomatic treatment planningdeep reinforcement learningexplainable artificial intelligenceintegrated gradient method

Identifiers

PMID41308315
PMCPMC12703622

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.