Evidence map›Paper›PMID 41281236›Full record

ArticleArXiv2025

Towards Human-Centric Intelligent Treatment Planning for Radiation Therapy.

Adnan Jafar, Xun Jia

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Adnan JafarDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA.
Xun JiaDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA.

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
Adversarially Based Virtual CT Workflow for Evaluation of AI in Medical ImagingR01EB032716 · NIBIB · RENSSELAER POLYTECHNIC INSTITUTE · PI JIA, XUN, MUELLER, KLAUS · 2022 to 2025
$2.5M
Precise image guidance for liver cancer stereotactic body radiotherapy using element-resolved motion-compensated cone beam CTR01CA227289 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI JIA, XUN · 2018 to 2022
$2.0M
NCI NIH HHS R01 CA227289NCI NIH HHS R01 CA254377NCI NIH HHS R37 CA214639NIBIB NIH HHS R01 EB032716
6 · The paper itself

Abstract

Current radiation therapy treatment planning is limited by suboptimal plan quality, inefficiency, and high costs. This perspective paper explores the complexity of treatment planning and introduces Human-Centric Intelligent Treatment Planning (HCITP), an AI-driven framework under human oversight, which integrates clinical guidelines, automates plan generation, and enables direct interactions with operators. We expect that HCITP will enhance efficiency, potentially reducing planning time to minutes, and will deliver personalized, high-quality plans. Challenges and potential solutions are discussed.

Identifiers

PMID41281236
PMCPMC12633150

What Socratic 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 Socratic graph.