{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T12:31:20Z","timestamp":1786710680012,"version":"build-2736575974"},"reference-count":28,"publisher":"Elsevier BV","issue":"8","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advancesradonc.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advances in Radiation Oncology"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.adro.2026.102036","type":"journal-article","created":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T16:14:47Z","timestamp":1775060087000},"page":"102036","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development and Clinical Validation of a Protocol-Agnostic Machine Learning Platform for Automated Treatment Planning in External Beam Radiation Therapy"],"prefix":"10.1016","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4510-2516","authenticated-orcid":false,"given":"Julie K.","family":"Shade","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pranav","family":"Lakshminarayanan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Hoban","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Bowers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"Gorman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saida Muktar","family":"Reshid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Lilieholm","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Velten","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siddharth","family":"Kapoor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tyler","family":"Smith","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Murray","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wolfgang A.","family":"Tom\u00e9","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harry","family":"Quon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel Y.","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Todd","family":"McNutt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.adro.2026.102036_bib0001","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/j.prro.2011.11.012","article-title":"Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems","volume":"2","author":"Nelms","year":"2012","journal-title":"Pract Radiat Oncol"},{"key":"10.1016\/j.adro.2026.102036_bib0002","doi-asserted-by":"crossref","first-page":"5497","DOI":"10.1118\/1.3253464","article-title":"Patient geometry-driven information retrieval for IMRT treatment plan quality control","volume":"36","author":"Wu","year":"2009","journal-title":"Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0003","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1002\/acm2.13337","article-title":"Knowledge-based radiation treatment planning: A data-driven method survey","volume":"22","author":"Momin","year":"2021","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0004","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.radonc.2011.05.025","article-title":"Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma","volume":"102","author":"Petit","year":"2012","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.adro.2026.102036_bib0005","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1038\/s41598-018-37741-x","article-title":"A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning","volume":"9","author":"Nguyen","year":"2019","journal-title":"Sci Rep"},{"key":"10.1016\/j.adro.2026.102036_bib0006","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ab039b","article-title":"3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture","volume":"64","author":"Nguyen","year":"2019","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.adro.2026.102036_bib0007","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1118\/1.4938583","article-title":"Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy","volume":"43","author":"Shiraishi","year":"2016","journal-title":"Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0008","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1200\/CCI.20.00093","article-title":"ORBIT-RT: A real-time, open platform for knowledge-based quality control of radiotherapy treatment planning","volume":"5","author":"Covele","year":"2021","journal-title":"JCO Clin Cancer Inform"},{"key":"10.1016\/j.adro.2026.102036_bib0009","doi-asserted-by":"crossref","first-page":"2760","DOI":"10.1002\/mp.13526","article-title":"Knowledge-based planning for intensity-modulated radiation therapy: A review of data-driven approaches","volume":"46","author":"Ge","year":"2019","journal-title":"Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0010","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1002\/jmrs.420","article-title":"Rolling out RapidPlan: What we\u2019ve learnt","volume":"67","author":"van Gysen","year":"2020","journal-title":"J Med Radiat Sci"},{"key":"10.1016\/j.adro.2026.102036_bib0011","doi-asserted-by":"crossref","first-page":"7446","DOI":"10.1118\/1.4761864","article-title":"Predicting dose-volume histograms for organs-at-risk in IMRT planning","volume":"39","author":"Appenzoller","year":"2012","journal-title":"Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0012","doi-asserted-by":"crossref","first-page":"5617","DOI":"10.1002\/mp.12556","article-title":"Outlier identification in radiation therapy knowledge-based planning: A study of pelvic cases","volume":"44","author":"Sheng","year":"2017","journal-title":"Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0013","doi-asserted-by":"crossref","first-page":"934","DOI":"10.1002\/mp.13316","article-title":"Knowledge-based dose prediction models for head and neck cancer are strongly affected by interorgan dependency and dataset inconsistency","volume":"46","author":"Wang","year":"2019","journal-title":"Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0014","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1016\/j.ijrobp.2014.11.014","article-title":"Evaluation of a knowledge-based planning solution for head and neck cancer","volume":"91","author":"Tol","year":"2015","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0015","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/s13014-018-0996-z","article-title":"Knowledge-based IMRT planning for individual liver cancer patients using a novel specific model","volume":"13","author":"Yu","year":"2018","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.adro.2026.102036_bib0016","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1002\/acm2.12322","article-title":"Creation of knowledge-based planning models intended for large scale distribution: Minimizing the effect of outlier plans","volume":"19","author":"Alpuche Aviles","year":"2018","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0017","doi-asserted-by":"crossref","first-page":"e218","DOI":"10.1016\/j.prro.2018.11.007","article-title":"Multi-institutional validation of a knowledge-based planning model for patients enrolled in RTOG 0617: Implications for plan quality controls in cooperative group trials","volume":"9","author":"Kavanaugh","year":"2019","journal-title":"Pract Radiat Oncol"},{"key":"10.1016\/j.adro.2026.102036_bib0018","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.ijrobp.2015.11.011","article-title":"Effect of dosimetric outliers on the performance of a commercial knowledge-based planning solution","volume":"94","author":"Delaney","year":"2016","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0019","doi-asserted-by":"crossref","first-page":"6868","DOI":"10.1118\/1.4757927","article-title":"Quantitative analysis of the factors which affect the interpatient organ-at-risk dose sparing variation in IMRT plans","volume":"39","author":"Yuan","year":"2012","journal-title":"Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0020","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/0169-7439(87)80084-9","article-title":"Principal component analysis","volume":"2","author":"Wold","year":"1987","journal-title":"Chemom Intell Lab Syst"},{"key":"10.1016\/j.adro.2026.102036_bib0021","series-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2010. MICCAI 2010. Lecture Notes in Computer Science","first-page":"521","article-title":"A statistical approach for achievable dose querying in IMRT planning","volume":"6363","author":"Simari","year":"2010"},{"key":"10.1016\/j.adro.2026.102036_bib0022","doi-asserted-by":"crossref","first-page":"667","DOI":"10.3390\/diagnostics13040667","article-title":"Automated contouring and planning in radiation therapy: what is \u2018Clinically Acceptable\u2019?","volume":"13","author":"Baroudi","year":"2023","journal-title":"Diagnostics (Basel)"},{"key":"10.1016\/j.adro.2026.102036_bib0023","doi-asserted-by":"crossref","first-page":"736","DOI":"10.3889\/oamjms.2017.161","article-title":"Conformity index and homogeneity index of the postoperative whole breast radiotherapy","volume":"5","author":"Petrova","year":"2017","journal-title":"Open Access Maced J Med Sci"},{"key":"10.1016\/j.adro.2026.102036_bib0024","doi-asserted-by":"crossref","DOI":"10.1002\/acm2.13609","article-title":"Organ-at-risk dose prediction using a machine learning algorithm: Clinical validation and treatment planning benefit for lung SBRT","volume":"23","author":"Brodin","year":"2022","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.adro.2026.102036_bib0025","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy function approximation: A gradient boosting machine","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann Statist"},{"key":"10.1016\/j.adro.2026.102036_bib0026","series-title":"Classification and Regression Trees","author":"Breiman","year":"2017"},{"key":"10.1016\/j.adro.2026.102036_bib0027","series-title":"XXth International Conference on the Use of Computers in Radiation Therapy","article-title":"AI-guided unattended plan generation","author":"Velten","year":"2024"},{"key":"10.1016\/j.adro.2026.102036_bib0028","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1186\/s13014-018-1113-z","article-title":"Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer","volume":"13","author":"Krayenbuehl","year":"2018","journal-title":"Radiat Oncol"}],"container-title":["Advances in Radiation Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2452109426000436?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2452109426000436?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T11:35:55Z","timestamp":1786707355000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2452109426000436"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":28,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["S2452109426000436"],"URL":"https:\/\/doi.org\/10.1016\/j.adro.2026.102036","relation":{},"ISSN":["2452-1094"],"issn-type":[{"value":"2452-1094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Development and Clinical Validation of a Protocol-Agnostic Machine Learning Platform for Automated Treatment Planning in External Beam Radiation Therapy","name":"articletitle","label":"Article Title"},{"value":"Advances in Radiation Oncology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.adro.2026.102036","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc. on behalf of American Society for Radiation Oncology.","name":"copyright","label":"Copyright"}],"article-number":"102036"}}