Standardising AI Model Reporting for Radiotherapy: A Domain-Specific Model Card

Artificial intelligence (AI) is becoming ubiquitous in radiation therapy (RT), with both in-house and commercial models reaching clinical practice. However, there is a lack of transparency when transferring these models from development to end-users, due to insufficient documentation of their specifications and performance. This hinders clinicians' trust, model comparability and selection. Tools like model cards [1] and datasheets [2] aim to overcome this, but despite recent efforts to adopt them in RT [3], there is not yet a comprehensive, practical, and domain-specific standard for reporting AI models. We present an RT-specific model card to standardise documentation and increase transparency, operability, and trust in clinically-used AI models.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-04
DOI
https://doi.org/10.5281/zenodo.15336016
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Standardising AI Model Reporting for Radiotherapy: A Domain-Specific Model Card

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Standardising AI Model Reporting for Radiotherapy: A Domain-Specific Model Card

article en

Abstract

Artificial intelligence (AI) is becoming ubiquitous in radiation therapy (RT), with both in-house and commercial models reaching clinical practice. However, there is a lack of transparency when transferring these models from development to end-users, due to insufficient documentation of their specifications and performance. This hinders clinicians' trust, model comparability and selection. Tools like model cards [1] and datasheets [2] aim to overcome this, but despite recent efforts to adopt them in RT [3], there is not yet a comprehensive, practical, and domain-specific standard for reporting AI models. We present an RT-specific model card to standardise documentation and increase transparency, operability, and trust in clinically-used AI models.

Zenodo (CERN European Organization for Nuclear Research)
UCLouvain (BE)
Openalex Percentile: Top 60%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Standardising AI Model Reporting for Radiotherapy: A Domain-Specific Model Card · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS