{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:51:10Z","timestamp":1791348670414,"version":"4.3.1"},"reference-count":46,"publisher":"Elsevier BV","issue":"3","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,2,3]],"date-time":"2027-02-03T00:00:00Z","timestamp":1801612800000},"content-version":"am","delay-in-days":339,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100018047","name":"NRG Oncology","doi-asserted-by":"publisher","award":["U54CA274513"],"award-info":[{"award-number":["U54CA274513"]}],"id":[{"id":"10.13039\/100018047","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100018047","name":"NRG Oncology","doi-asserted-by":"publisher","award":["R01EB032680"],"award-info":[{"award-number":["R01EB032680"]}],"id":[{"id":"10.13039\/100018047","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100018047","name":"NRG Oncology","doi-asserted-by":"publisher","award":["R01CA272991"],"award-info":[{"award-number":["R01CA272991"]}],"id":[{"id":"10.13039\/100018047","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100018047","name":"NRG Oncology","doi-asserted-by":"publisher","award":["R01DE033512"],"award-info":[{"award-number":["R01DE033512"]}],"id":[{"id":"10.13039\/100018047","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006384","name":"American College of Radiology Imaging Network","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006384","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000005","name":"U.S. Department of Defense","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000005","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000043","name":"American Association for Cancer Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000043","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001960","name":"American Society for Radiation Oncology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001960","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007313","name":"University of Texas MD Anderson Cancer Center","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007313","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007325","name":"American Association of Physicists in Medicine","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007325","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000871","name":"Mayo Clinic","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100011886","name":"Dubai Harvard Foundation for Medical Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100011886","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","redjournal.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Radiation Oncology*Biology*Physics"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.ijrobp.2025.09.063","type":"journal-article","created":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T22:52:58Z","timestamp":1760223178000},"page":"856-867","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"title":["Clinically Interpretable Survival Risk Stratification in Head and Neck Cancer Using Bayesian Networks and Markov Blankets"],"prefix":"10.1016","volume":"124","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0886-655X","authenticated-orcid":false,"given":"Keyur D.","family":"Shah","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ibrahim","family":"Chamseddine","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohan","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sibo","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anees","family":"Dhabaan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hania","family":"Al-Hallaq","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David S.","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harald","family":"Paganetti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofeng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ijrobp.2025.09.063_bib0001","first-page":"209","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J Clin"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0002","first-page":"122","article-title":"Head and neck cancers-Major changes in the American Joint Committee on Cancer eighth edition cancer staging manual","volume":"67","author":"Lydiatt","year":"2017","journal-title":"CA Cancer J Clin"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0003","doi-asserted-by":"crossref","first-page":"2","DOI":"10.6004\/jnccn.2025.0007","article-title":"NCCN guidelines\u00ae insights: Head and neck cancers, version 2.2025: Featured updates to the NCCN guidelines","volume":"23","author":"Colevas","year":"2025","journal-title":"J Natl Compr Canc Netw"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0004","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.radonc.2009.04.014","article-title":"Meta-analysis of chemotherapy in head and neck cancer (MACH-NC): An update on 93 randomised trials and 17,346 patients","volume":"92","author":"Pignon","year":"2009","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0005","doi-asserted-by":"crossref","first-page":"3858","DOI":"10.1200\/JCO.2014.55.3925","article-title":"Randomized phase III trial to test accelerated versus standard fractionation in combination with concurrent cisplatin for head and neck carcinomas in the Radiation Therapy Oncology Group 0129 trial: Long-term report of efficacy and toxicity","volume":"32","author":"Nguyen-Tan","year":"2014","journal-title":"J Clin Oncol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0006","doi-asserted-by":"crossref","first-page":"338","DOI":"10.3390\/cancers13020338","article-title":"Recent advances and future directions in clinical management of head and neck squamous cell carcinoma","volume":"13","author":"Muzaffar","year":"2021","journal-title":"Cancers"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0007","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.semcancer.2023.07.002","article-title":"Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives","volume":"95","author":"Zhong","year":"2023","journal-title":"Semin Cancer Biol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0008","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1056\/NEJMoa0912217","article-title":"Human papillomavirus and survival of patients with oropharyngeal cancer","volume":"363","author":"Ang","year":"2010","journal-title":"N Engl J Med"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0009","series-title":"Probabilistic Reasoning in Intelligent Systems","author":"Pearl","year":"1988"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0010","series-title":"Probabilistic Graphical Models: Principles and Techniques","author":"Koller","year":"2010"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0011","series-title":"Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference","author":"Pearl","year":"2014"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0012","series-title":"Algorithms for Large Scale Markov Blanket Discovery","author":"Tsamardinos","year":"2003"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0013","doi-asserted-by":"crossref","first-page":"3101","DOI":"10.1002\/mp.16972","article-title":"RADCURE: An open-source head and neck cancer CT dataset for clinical radiation therapy insights","volume":"51","author":"Welch","year":"2024","journal-title":"Med Phys"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0014","doi-asserted-by":"crossref","first-page":"1140","DOI":"10.1158\/2767-9764.CRC-22-0152","article-title":"Multi-institutional prognostic modeling in head and neck cancer: Evaluating impact and generalizability of deep learning and radiomics","volume":"3","author":"Kazmierski","year":"2023","journal-title":"Cancer Res Commun"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0015","doi-asserted-by":"crossref","first-page":"55","DOI":"10.7326\/M14-0697","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement","volume":"162","author":"Collins","year":"2015","journal-title":"Ann Intern Med"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0016","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.230024","article-title":"TotalSegmentator: Robust segmentation of 104 anatomic structures in CT images","volume":"5","author":"Wasserthal","year":"2023","journal-title":"Radiol Artif Intell"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0017","doi-asserted-by":"crossref","first-page":"4424","DOI":"10.1158\/1078-0432.CCR-24-1215","article-title":"Decoding patient heterogeneity influencing radiation-induced brain necrosis","volume":"30","author":"Chamseddine","year":"2024","journal-title":"Clin Cancer Res"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0018","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1093\/biomet\/87.4.954","article-title":"A new family of power transformations to improve normality or symmetry","volume":"87","author":"Yeo","year":"2000","journal-title":"Biometrika"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0019","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","article-title":"A new look at the statistical model identification","volume":"19","author":"Akaike","year":"1974","journal-title":"IEEE Trans Autom Control"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0020","doi-asserted-by":"crossref","first-page":"2709","DOI":"10.1007\/s00405-017-4533-8","article-title":"How phenotype guides management of non-conventional squamous cell carcinomas of the larynx?","volume":"274","author":"L\u00f3pez","year":"2017","journal-title":"Eur Arch Otorhinolaryngol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0021","doi-asserted-by":"crossref","first-page":"1967","DOI":"10.1016\/j.ejca.2010.04.004","article-title":"Nasopharyngeal carcinoma: The next challenges","volume":"46","author":"Razak","year":"2010","journal-title":"Eur J Cancer"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0022","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1002\/hed.21613","article-title":"Current trends in initial management of hypopharyngeal cancer: The declining use of open surgery","volume":"34","author":"Takes","year":"2012","journal-title":"Head Neck"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0023","series-title":"AJCC Cancer Staging Manual","article-title":"American Joint Committee on Cancer","year":"2017"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0024","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.radonc.2013.10.010","article-title":"Delineation of the neck node levels for head and neck tumors: A 2013 update. DAHANCA, EORTC, HKNPCSG, NCIC CTG, NCRI, RTOG, TROG consensus guidelines","volume":"110","author":"Gr\u00e9goire","year":"2014","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0025","doi-asserted-by":"crossref","first-page":"6994","DOI":"10.1038\/s41598-019-43372-7","article-title":"Deep learning-based survival prediction of oral cancer patients","volume":"9","author":"Kim","year":"2019","journal-title":"Sci Rep"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0026","doi-asserted-by":"crossref","first-page":"1185","DOI":"10.1109\/JBHI.2022.3219445","article-title":"3D-IncNet: Head and neck (H&N) primary tumors segmentation and survival prediction","volume":"28","author":"Qayyum","year":"2024","journal-title":"IEEE J Biomed Health Inform"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0027","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1016\/j.ijrobp.2023.10.022","article-title":"Vision transformer-based multilabel survival prediction for oropharynx cancer after radiation therapy","volume":"118","author":"Chen","year":"2024","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2023.107714","article-title":"Fusion-based tensor radiomics using reproducible features: Application to survival prediction in head and neck cancer","volume":"240","author":"Salmanpour","year":"2023","journal-title":"Comput Methods Programs Biomed"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.radonc.2025.110852","article-title":"PET and CT based DenseNet outperforms advanced deep learning models for outcome prediction of oropharyngeal cancer","volume":"207","author":"Ma","year":"2025","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0030","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.radonc.2017.02.004","article-title":"Unraveling biophysical interactions of radiation pneumonitis in non-small-cell lung cancer via Bayesian network analysis","volume":"123","author":"Luo","year":"2017","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0031","doi-asserted-by":"crossref","first-page":"3980","DOI":"10.1002\/mp.13029","article-title":"A multiobjective Bayesian networks approach for joint prediction of tumor local control and radiation pneumonitis in nonsmall-cell lung cancer (NSCLC) for response-adapted radiotherapy","volume":"45","author":"Luo","year":"2018","journal-title":"Med Phys"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0032","doi-asserted-by":"crossref","first-page":"2735","DOI":"10.1088\/0031-9155\/60\/7\/2735","article-title":"Bayesian network models for error detection in radiotherapy plans","volume":"60","author":"Kalet","year":"2015","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0033","doi-asserted-by":"crossref","first-page":"2006","DOI":"10.1002\/mp.13515","article-title":"Characterization of a Bayesian network-based radiotherapy plan verification model","volume":"46","author":"Luk","year":"2019","journal-title":"Med Phys"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0034","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ac88b3","article-title":"Personalized mid-course FDG-PET based adaptive treatment planning for non-small cell lung cancer using machine learning and optimization","volume":"67","author":"Ajdari","year":"2022","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0035","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.phro.2022.03.002","article-title":"Bayesian network structure for predicting local tumor recurrence in rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery","volume":"22","author":"Osong","year":"2022","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0036","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1016\/j.ijrobp.2016.08.046","article-title":"The impact of radiation treatment time on survival in patients with head and neck cancer","volume":"96","author":"Shaikh","year":"2016","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0037","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1016\/j.ijrobp.2017.02.218","article-title":"Final report of a prospective randomized trial to evaluate the dose-response relationship for postoperative radiation therapy and pathologic risk groups in patients with head and neck cancer","volume":"98","author":"Rosenthal","year":"2017","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0038","doi-asserted-by":"crossref","DOI":"10.1016\/j.oraloncology.2020.104819","article-title":"Duration of radiation therapy is associated with worse survival in head and neck cancer","volume":"108","author":"Mazul","year":"2020","journal-title":"Oral Oncol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0039","doi-asserted-by":"crossref","first-page":"14593","DOI":"10.18632\/aging.103508","article-title":"Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment 18F-PET\/CT","volume":"12","author":"Liu","year":"2020","journal-title":"Aging"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0040","first-page":"287","article-title":"Progression free survival prediction for head and neck cancer using deep learning based on clinical and PET\/CT imaging data","volume":"13209","author":"Naser","year":"2022","journal-title":"Head Neck Tumor Segm Chall (2021)"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2022.106948","article-title":"Deep learning based time-to-event analysis with PET, CT and joint PET\/CT for head and neck cancer prognosis","volume":"222","author":"Wang","year":"2022","journal-title":"Comput Methods Programs Biomed"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0042","doi-asserted-by":"crossref","first-page":"1932","DOI":"10.3390\/cancers15071932","article-title":"From head and neck tumour and lymph node segmentation to survival prediction on PET\/CT: An end-to-end framework featuring uncertainty, fairness, and multi-region multi-modal radiomics","volume":"15","author":"Salahuddin","year":"2023","journal-title":"Cancers"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0043","doi-asserted-by":"crossref","first-page":"778","DOI":"10.3174\/ajnr.A2376","article-title":"Prediction of disease-free survival in patients with squamous cell carcinomas of the head and neck using dynamic contrast-enhanced MR imaging","volume":"32","author":"Chawla","year":"2011","journal-title":"AJNR Am J Neuroradiol"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0044","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1148\/radiol.2018180200","article-title":"Radiomic MRI phenotyping of glioblastoma: Improving survival prediction","volume":"289","author":"Bae","year":"2018","journal-title":"Radiology"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0045","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1148\/radiol.14131691","article-title":"Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: Focus on the nonenhancing component of the tumor","volume":"272","author":"Jain","year":"2014","journal-title":"Radiology"},{"key":"10.1016\/j.ijrobp.2025.09.063_bib0046","doi-asserted-by":"crossref","DOI":"10.3389\/frai.2023.1222612","article-title":"Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas","volume":"6","author":"Chaudhuri","year":"2023","journal-title":"Front Artif Intell"}],"container-title":["International Journal of Radiation Oncology*Biology*Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360301625063369?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360301625063369?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T04:08:03Z","timestamp":1773288483000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0360301625063369"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":46,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["S0360301625063369"],"URL":"https:\/\/doi.org\/10.1016\/j.ijrobp.2025.09.063","relation":{},"ISSN":["0360-3016"],"issn-type":[{"value":"0360-3016","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Clinically Interpretable Survival Risk Stratification in Head and Neck Cancer Using Bayesian Networks and Markov Blankets","name":"articletitle","label":"Article Title"},{"value":"International Journal of Radiation Oncology*Biology*Physics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ijrobp.2025.09.063","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}