{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T04:23:56Z","timestamp":1787804636844,"version":"build-2784847793"},"reference-count":52,"publisher":"Elsevier BV","issue":"5","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["practicalradonc.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Practical Radiation Oncology"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.prro.2025.04.009","type":"journal-article","created":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T20:40:03Z","timestamp":1745959203000},"page":"e412-e423","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":7,"title":["Assessing ChatGPT for Clinical Decision-Making in Radiation Oncology, With Open-Ended Questions and Images"],"prefix":"10.1016","volume":"15","author":[{"given":"Wei-Kai","family":"Chuang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yung-Shuo","family":"Kao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yen-Ting","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6227-6923","authenticated-orcid":false,"given":"Cho-Yin","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.prro.2025.04.009_bib0001","unstructured":"OpenAI. Introducing ChatGPT. 2022. https:\/\/openai.com\/index\/chatgpt\/"},{"key":"10.1016\/j.prro.2025.04.009_bib0002","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume":"35","author":"Ouyang","year":"2022","journal-title":"Adv Neural Inf Process Syst"},{"key":"10.1016\/j.prro.2025.04.009_bib0003","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1038\/s41586-023-05881-4","article-title":"Foundation models for generalist medical artificial intelligence","volume":"616","author":"Moor","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.prro.2025.04.009_bib0004","doi-asserted-by":"crossref","first-page":"2652","DOI":"10.1007\/s10439-023-03285-z","article-title":"Do people use ChatGPT to replace doctor? A google trends analysis","volume":"51","author":"Kao","year":"2023","journal-title":"Ann Biomed Eng"},{"key":"10.1016\/j.prro.2025.04.009_bib0005","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2023.1268915","article-title":"Applications of large language models in cancer care: Current evidence and future perspectives","volume":"13","author":"Iannantuono","year":"2023","journal-title":"Front Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0006","doi-asserted-by":"crossref","first-page":"pkad015","DOI":"10.1093\/jncics\/pkad015","article-title":"Using ChatGPT to evaluate cancer myths and misconceptions: Artificial intelligence and cancer information","volume":"7","author":"Johnson","year":"2023","journal-title":"JNCI Cancer Spectr"},{"key":"10.1016\/j.prro.2025.04.009_bib0007","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/j.ijrobp.2023.03.075","article-title":"ChatGPT: Can a natural language processing tool be trusted for radiation oncology use?","volume":"116","author":"Ebrahimi","year":"2023","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.prro.2025.04.009_bib0008","doi-asserted-by":"crossref","first-page":"1237","DOI":"10.1093\/jamia\/ocad072","article-title":"Using AI-generated suggestions from ChatGPT to optimize clinical decision support","volume":"30","author":"Liu","year":"2023","journal-title":"J Am Med Inform Assoc"},{"key":"10.1016\/j.prro.2025.04.009_bib0009","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1056\/NEJMsr2214184","article-title":"Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine","volume":"388","author":"Lee","year":"2023","journal-title":"N Engl J Med"},{"key":"10.1016\/j.prro.2025.04.009_bib0010","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.232756","article-title":"Chatbots and large language models in radiology: A practical primer for clinical and research applications","volume":"310","author":"Bhayana","year":"2024","journal-title":"Radiology"},{"key":"10.1016\/j.prro.2025.04.009_bib0011","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1097\/PAP.0000000000000406","article-title":"Application of ChatGPT in routine diagnostic pathology: Promises, pitfalls, and potential future directions","volume":"31","author":"Schukow","year":"2024","journal-title":"Adv Anat Pathol"},{"key":"10.1016\/j.prro.2025.04.009_bib0012","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pdig.0000198","article-title":"Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models","volume":"2","author":"Kung","year":"2023","journal-title":"PLOS Digit Health"},{"key":"10.1016\/j.prro.2025.04.009_bib0013","doi-asserted-by":"crossref","DOI":"10.2196\/57594","article-title":"Correction: How does ChatGPT perform on the United States Medical Licensing Examination (USMLE)? The implications of large language models for medical education and knowledge assessment","volume":"10","author":"Gilson","year":"2024","journal-title":"JMIR Med Educ"},{"key":"10.1016\/j.prro.2025.04.009_bib0014","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1007\/s10439-023-03308-9","article-title":"Use of ChatGPT on Taiwan's examination for medical doctors","volume":"52","author":"Kao","year":"2024","journal-title":"Ann Biomed Eng"},{"key":"10.1016\/j.prro.2025.04.009_bib0015","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.230582","article-title":"Performance of ChatGPT on a radiology board-style examination: Insights into current strengths and limitations","volume":"307","author":"Bhayana","year":"2023","journal-title":"Radiology"},{"key":"10.1016\/j.prro.2025.04.009_bib0016","doi-asserted-by":"crossref","first-page":"2817","DOI":"10.1007\/s00330-023-10213-1","article-title":"ChatGPT makes medicine easy to swallow: An exploratory case study on simplified radiology reports","volume":"34","author":"Jeblick","year":"2024","journal-title":"Eur Radiol"},{"key":"10.1016\/j.prro.2025.04.009_bib0017","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s42492-023-00136-5","article-title":"Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential","volume":"6","author":"Lyu","year":"2023","journal-title":"Vis Comput Ind Biomed Art"},{"key":"10.1016\/j.prro.2025.04.009_bib0018","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1002\/ohn.489","article-title":"Accuracy of ChatGPT-generated information on head and neck and oromaxillofacial surgery: A multicenter collaborative analysis","volume":"170","author":"Vaira","year":"2024","journal-title":"Otolaryngol Head Neck Surg"},{"key":"10.1016\/j.prro.2025.04.009_bib0019","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2023.36483","article-title":"Accuracy and reliability of chatbot responses to physician questions","volume":"6","author":"Goodman","year":"2023","journal-title":"JAMA Netw Open"},{"key":"10.1016\/j.prro.2025.04.009_bib0020","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1001\/jamaoncol.2023.2954","article-title":"Use of artificial intelligence chatbots for cancer treatment information","volume":"9","author":"Chen","year":"2023","journal-title":"JAMA Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0021","doi-asserted-by":"crossref","first-page":"721","DOI":"10.3350\/cmh.2023.0089","article-title":"Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma","volume":"29","author":"Yeo","year":"2023","journal-title":"Clin Mol Hepatol"},{"key":"10.1016\/j.prro.2025.04.009_bib0022","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1111\/his.15100","article-title":"Bridging bytes and biopsies: A comparative analysis of ChatGPT and histopathologists in pathology diagnosis and collaborative potential","volume":"84","author":"Oon","year":"2024","journal-title":"Histopathology"},{"key":"10.1016\/j.prro.2025.04.009_bib0023","article-title":"Evaluating GPT-4V (GPT-4 with Vision) on detection of radiologic findings on chest radiographs","volume":"311","author":"Zhou","year":"2024","journal-title":"Radiology"},{"key":"10.1016\/j.prro.2025.04.009_bib0024","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1007\/s00330-024-11035-5","article-title":"Assessing GPT-4 multimodal performance in radiological image analysis","volume":"35","author":"Brin","year":"2025","journal-title":"Eur Radiol"},{"key":"10.1016\/j.prro.2025.04.009_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.clinimag.2024.110101","article-title":"When vision meets reality: Exploring the clinical applicability of GPT-4 with vision","volume":"108","author":"Deng","year":"2024","journal-title":"Clin Imaging"},{"key":"10.1016\/j.prro.2025.04.009_bib0026","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2023.1219326","article-title":"Evaluating large language models on a highly-specialized topic, radiation oncology physics","volume":"13","author":"Holmes","year":"2023","journal-title":"Front Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0027","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2023.1265024","article-title":"Benchmarking ChatGPT-4 on a radiation oncology in-training exam and Red Journal Gray Zone cases: Potentials and challenges for AI-assisted medical education and decision making in radiation oncology","volume":"13","author":"Huang","year":"2023","journal-title":"Front Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0028","article-title":"Exploring capabilities of large language models such as ChatGPT in radiation oncology","volume":"9","author":"Dennst\u00e4dt","year":"2024","journal-title":"Adv Radiat Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0029","doi-asserted-by":"crossref","first-page":"e515","DOI":"10.1016\/j.prro.2024.04.017","article-title":"Benchmarking a foundation large language model on its ability to relabel structure names in accordance with the American Association of Physicists in Medicine task group-263 Report","volume":"14","author":"Holmes","year":"2024","journal-title":"Pract Radiat Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.radonc.2023.109978","article-title":"Pilot applications of GPT-4 in radiation oncology: Summarizing patient symptom intake and targeted chatbot applications","volume":"190","author":"Wu","year":"2024","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0031","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2024.4630","article-title":"Quality of large language model responses to radiation oncology patient care questions","volume":"7","author":"Yalamanchili","year":"2024","journal-title":"JAMA Netw Open"},{"key":"10.1016\/j.prro.2025.04.009_bib0032","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1016\/j.ijrobp.2023.10.020","article-title":"Current strengths and weaknesses of ChatGPT as a resource for radiation oncology patients and providers","volume":"118","author":"Floyd","year":"2024","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.prro.2025.04.009_bib0033","doi-asserted-by":"crossref","DOI":"10.1016\/j.radonc.2024.110645","article-title":"Evaluating ChatGPT\u2019s competency in radiation oncology: A comprehensive assessment across clinical scenarios","volume":"202","author":"Ramadan","year":"2025","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.prro.2025.04.009_bib0034","year":"2024","journal-title":"GPT-4O System Card"},{"key":"10.1016\/j.prro.2025.04.009_bib0035","year":"2023","journal-title":"GPT-4V System Card"},{"key":"10.1016\/j.prro.2025.04.009_bib0036","year":"2023","journal-title":"GPT-4 System Card"},{"key":"10.1016\/j.prro.2025.04.009_bib0037","article-title":"A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation","author":"Li","year":"2024","journal-title":"arXiv preprint arXiv:2404.03253"},{"key":"10.1016\/j.prro.2025.04.009_bib0038","doi-asserted-by":"crossref","first-page":"2009","DOI":"10.3174\/ajnr.A7285","article-title":"Intraindividual comparison between the contrast-enhanced golden-angle radial sparse parallel sequence and the conventional fat-suppressed contrast-enhanced T1-weighted spin-echo sequence for head and neck MRI","volume":"42","author":"Hur","year":"2021","journal-title":"AJNR Am J Neuroradiol"},{"key":"10.1016\/j.prro.2025.04.009_bib0039","first-page":"93","article-title":"The eighth edition AJCC cancer staging manual: Continuing to build a bridge from a population-based to a more \"personalized\" approach to cancer staging","volume":"67","author":"Amin","year":"2017","journal-title":"CA Cancer J Clin"},{"key":"10.1016\/j.prro.2025.04.009_bib0040","doi-asserted-by":"crossref","first-page":"276","DOI":"10.11613\/BM.2012.031","article-title":"Interrater reliability: The kappa statistic","volume":"22","author":"McHugh","year":"2012","journal-title":"Biochem Med"},{"key":"10.1016\/j.prro.2025.04.009_bib0041","doi-asserted-by":"crossref","first-page":"e3","DOI":"10.5395\/rde.2024.49.e3","article-title":"Sample size determination for conducting a pilot study to assess reliability of a questionnaire","volume":"49","author":"Bujang","year":"2024","journal-title":"Restor Dent Endod"},{"key":"10.1016\/j.prro.2025.04.009_bib0042","article-title":"Guidelines of the minimum sample size requirements for Kappa agreement test","volume":"14","author":"Bujang","year":"2017","journal-title":"Epidemiol Biostatistics Public Health"},{"key":"10.1016\/j.prro.2025.04.009_bib0043","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.canrad.2023.11.005","article-title":"Evaluating ChatGPT to test its robustness as an interactive information database of radiation oncology and to assess its responses to common queries from radiotherapy patients: A single institution investigation","volume":"28","author":"Pandey","year":"2024","journal-title":"Cancer Radiother"},{"key":"10.1016\/j.prro.2025.04.009_bib0044","doi-asserted-by":"crossref","first-page":"124","DOI":"10.3350\/cmh.2023.0470","article-title":"Correspondence on Letter regarding \"Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma","volume":"30","author":"Yeo","year":"2024","journal-title":"Clin Mol Hepatol"},{"key":"10.1016\/j.prro.2025.04.009_bib0045","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.231040","article-title":"Diagnostic performance of ChatGPT from patient history and imaging findings on the diagnosis please quizzes","volume":"308","author":"Ueda","year":"2023","journal-title":"Radiology"},{"key":"10.1016\/j.prro.2025.04.009_bib0046","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.232346","article-title":"Testing the ability and limitations of ChatGPT to generate differential diagnoses from transcribed radiologic findings","volume":"313","author":"Sun","year":"2024","journal-title":"Radiology"},{"key":"10.1016\/j.prro.2025.04.009_bib0047","doi-asserted-by":"crossref","first-page":"1074","DOI":"10.1002\/jmri.27202","article-title":"Automatic T staging using weakly supervised deep learning for nasopharyngeal carcinoma on MR images","volume":"52","author":"Yang","year":"2020","journal-title":"J Magn Reson Imaging"},{"key":"10.1016\/j.prro.2025.04.009_bib0048","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1186\/s13054-023-04393-x","article-title":"Large language models and the perils of their hallucinations","volume":"27","author":"Azamfirei","year":"2023","journal-title":"Crit Care"},{"key":"10.1016\/j.prro.2025.04.009_bib0049","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1016\/j.ijrobp.2023.11.062","article-title":"Exploring the capabilities and limitations of large language models for radiation oncology decision support","volume":"118","author":"Putz","year":"2024","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.prro.2025.04.009_bib0050","unstructured":"Achiam J, Adler S, Agarwal S, et al. Gpt-4 technical report. arXiv preprint arXiv:2303.08774. 2023."},{"key":"10.1016\/j.prro.2025.04.009_bib0051","series-title":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","first-page":"2597","article-title":"Zero-shot diagnosis of unseen pulmonary diseases via spatial domain adaptive correction and guidance by ChatGPT-4o","author":"Wang","year":"2024"},{"key":"10.1016\/j.prro.2025.04.009_bib0052","unstructured":"Liu Z, Wang P, Li Y, et al. Radonc-gpt: A large language model for radiation oncology. arXiv preprint arXiv:2309.10160. 2023."}],"container-title":["Practical Radiation Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1879850025001158?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1879850025001158?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T08:42:14Z","timestamp":1756456934000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1879850025001158"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":52,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["S1879850025001158"],"URL":"https:\/\/doi.org\/10.1016\/j.prro.2025.04.009","relation":{},"ISSN":["1879-8500"],"issn-type":[{"value":"1879-8500","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Assessing ChatGPT for Clinical Decision-Making in Radiation Oncology, With Open-Ended Questions and Images","name":"articletitle","label":"Article Title"},{"value":"Practical Radiation Oncology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.prro.2025.04.009","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 American Society for Radiation Oncology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}