{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T11:01:03Z","timestamp":1789988463976,"version":"4.0.1"},"reference-count":31,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T00:00:00Z","timestamp":1789689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Children"],"abstract":"<jats:p>Background\/Objectives: Multimodal large language models (LLMs) can interpret clinical text and images, but their performance in pediatric rash assessment remains uncertain. This study compared the clinical utility, safety, information quality, diagnostic correctness, and readability of ChatGPT, Gemini and Grok. Methods: Fifteen content-validated pediatric rash vignettes with brief histories and anonymized photographs were submitted once to each platform using a standardized zero-shot prompt. Three pediatricians blinded to platform identity independently rated the 45 responses using a five-point Clinical Utility and Safety (CUS) scale and a five-item modified DISCERN instrument. Diagnostic correctness was assessed descriptively; platform comparisons used Friedman tests with Bonferroni-adjusted Wilcoxon tests when appropriate. Results: Overall, 82.2% of CUS ratings were in categories 4\u20135 and 83.0% of modified DISCERN scores were \u226520\/25; no rating was assigned to CUS category 1. Gemini and Grok had descriptively higher expert ratings than ChatGPT, but CUS did not differ significantly across platforms (p = 0.157), and although modified DISCERN differed globally (p = 0.038), no pairwise comparison remained significant after adjustment. In the single-query diagnostic assessment, at least one platform missed the reference diagnosis in 9\/15 vignettes, and all three missed porphyria. Gemini generated the longest responses, whereas Grok produced the most linguistically complex text; neither response length nor readability was associated with expert ratings. Conclusions: The three multimodal LLMs produced predominantly clinically acceptable responses, but performance varied by vignette and platform. Because each vignette\u2013platform combination was sampled once, diagnostic findings represent single-response observations rather than stable platform accuracy estimates. Clinical verification remains necessary.<\/jats:p>","DOI":"10.3390\/children13091272","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T09:01:38Z","timestamp":1789981298000},"page":"1272","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparative Expert Evaluation of Multimodal Large Language Models for Pediatric Rash Diagnosis: Clinical Utility, Safety, Information Quality, and Readability"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2602-3329","authenticated-orcid":false,"given":"Dilara","family":"Lahut","sequence":"first","affiliation":[{"name":"Department of Pediatrics, Zeynep Kamil Women and Children\u2019s Diseases Training and Research Hospital, University of Health Sciences, 34668 Istanbul, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5490-5361","authenticated-orcid":false,"given":"\u00d6zlem","family":"Erdede","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Zeynep Kamil Women and Children\u2019s Diseases Training and Research Hospital, University of Health Sciences, 34668 Istanbul, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9447-3583","authenticated-orcid":false,"given":"Rabia G\u00f6n\u00fcl","family":"Sezer Yamanel","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Zeynep Kamil Women and Children\u2019s Diseases Training and Research Hospital, University of Health Sciences, 34668 Istanbul, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.clindermatol.2019.01.009","article-title":"Viral exanthems in children: A great imitator","volume":"37","author":"Latour","year":"2019","journal-title":"Clin. Dermatol."},{"key":"ref_2","first-page":"1","article-title":"Emergency department management of rash and fever in the pediatric patient","volume":"17","author":"Philopena","year":"2020","journal-title":"Pediatr. Emerg. Med. Pract."},{"key":"ref_3","first-page":"e21764","article-title":"Challenges in evaluating pediatric fever and rash in the era of COVID-19 and multisystem inflammatory syndrome in children (MIS-C)","volume":"14","author":"Jarvill","year":"2022","journal-title":"Cureus"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e40031","DOI":"10.2196\/40031","article-title":"Artificial intelligence in emergency medicine: Viewpoint of current applications and foreseeable opportunities and challenges","volume":"25","author":"Chenais","year":"2023","journal-title":"J. Med. Internet Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e248895","DOI":"10.1001\/jamanetworkopen.2024.8895","article-title":"Use of a large language model to assess clinical acuity of adults in the emergency department","volume":"7","author":"Williams","year":"2024","journal-title":"JAMA Netw. Open"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e56110","DOI":"10.2196\/56110","article-title":"ChatGPT with GPT-4 outperforms emergency department physicians in diagnostic accuracy: Retrospective analysis","volume":"26","author":"Hoppe","year":"2024","journal-title":"J. Med. Internet Res."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Del Monte, F., Barolo, R., Circhetta, M., Delmonaco, A.G., Castagno, E., Pivetta, E., Bergamasco, L., Franco, M., Olmo, G., and Bondone, C. (2025). Diagnostic efficacy of large language models in the pediatric emergency department: A pilot study. Front. Digit. Health, 7.","DOI":"10.3389\/fdgth.2025.1624786"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"G\u00fcn, M. (2025). Can AI match emergency physicians in managing common emergency cases? A comparative performance evaluation. BMC Emerg. Med., 25.","DOI":"10.1186\/s12873-025-01303-y"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2613","DOI":"10.1038\/s41591-024-03097-1","article-title":"Evaluation and mitigation of the limitations of large language models in clinical decision-making","volume":"30","author":"Hager","year":"2024","journal-title":"Nat. Med."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Karampinis, E., Zafiriou, E., and Mantzaris, D. (2026). Artificial intelligence and special populations: Age considerations. Artificial Intelligence Applications in Dermatology: Dermatology ex Machina: Clinical Applications, Springer Nature.","DOI":"10.1007\/978-3-032-15614-3"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Jahn, A.S., Navarini, A.A., Cerminara, S.E., Kostner, L., Huber, S.M., Kunz, M., Maul, J.-T., Dummer, R., Sommer, S., and Neuner, A.D. (2022). Over-detection of melanoma-suspect lesions by a CE-certified smartphone app: Performance in comparison to dermatologists, 2D and 3D convolutional neural networks in a prospective data set of 1204 pigmented skin lesions involving patients\u2019 perception. Cancers, 14.","DOI":"10.3390\/cancers14153829"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5110","DOI":"10.5826\/dpc.1503a5110","article-title":"Assessment of a smartphone-based neural network application for the risk assessment of skin lesions under real-world conditions","volume":"15","author":"Efferl","year":"2025","journal-title":"Dermatol. Pract. Concept."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"5649","DOI":"10.1038\/s41467-024-50043-3","article-title":"Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4","volume":"15","author":"Zhou","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1007\/s00431-026-07044-9","article-title":"Diagnostic accuracy of artificial intelligence versus 263 pediatric clinicians for childhood exanthems","volume":"185","author":"Akcan","year":"2026","journal-title":"Eur. J. Pediatr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1097\/00006199-198611000-00017","article-title":"Determination and quantification of content validity","volume":"35","author":"Lynn","year":"1986","journal-title":"Nurs. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1002\/nur.20147","article-title":"The content validity index: Are you sure you know what\u2019s being reported? Critique and recommendations","volume":"29","author":"Polit","year":"2006","journal-title":"Res. Nurs. Health"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1136\/jech.53.2.105","article-title":"DISCERN: An instrument for judging the quality of written consumer health information on treatment choices","volume":"53","author":"Charnock","year":"1999","journal-title":"J. Epidemiol. Community Health"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1037\/h0057532","article-title":"A new readability yardstick","volume":"32","author":"Flesch","year":"1948","journal-title":"J. Appl. Psychol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1109\/TPC.2008.2007872","article-title":"Unlocking language: The classic readability studies","volume":"51","author":"DuBay","year":"2008","journal-title":"IEEE Trans. Prof. Commun."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1177\/15589447231168907","article-title":"Readability of online patient education materials for congenital hand differences","volume":"19","author":"Baldwin","year":"2024","journal-title":"Hand"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e16701","DOI":"10.2196\/16701","article-title":"Web-based health information following the renewal of the cervical screening program in Australia: Evaluation of readability, understandability, and credibility","volume":"22","author":"Mac","year":"2020","journal-title":"J. Med. Internet Res."},{"key":"ref_22","unstructured":"Readable (2026, July 30). Readability Formulas. Available online: https:\/\/readable.com\/readability\/readability-formulas\/."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A guideline of selecting and reporting intraclass correlation coefficients for reliability research","volume":"15","author":"Koo","year":"2016","journal-title":"J. Chiropr. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1080\/19312450709336664","article-title":"Answering the call for a standard reliability measure for coding data","volume":"1","author":"Hayes","year":"2007","journal-title":"Commun. Methods Meas."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"43758","DOI":"10.1038\/s41598-025-27235-y","article-title":"Multidimensional assessment of large language model responses to patient questions on gestational diabetes mellitus","volume":"15","author":"Mutlu","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1038\/s41598-023-50884-w","article-title":"Evaluation of the reliability and readability of ChatGPT-4 responses regarding hypothyroidism during pregnancy","volume":"14","author":"Onder","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1007\/s00464-025-12315-x","article-title":"ChatGPT and other large language models in laparoscopic cholecystectomy: A multidimensional audit of reliability, quality, and readability","volume":"40","author":"Korkmaz","year":"2026","journal-title":"Surg. Endosc."},{"key":"ref_28","first-page":"e78313","article-title":"Evaluating the quality and readability of generative artificial intelligence chatbot responses in the management of Achilles tendon rupture","volume":"17","author":"Collins","year":"2025","journal-title":"Cureus"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Temizsoy Korkmaz, F., Ok, F., Karip, B., and Kele\u015f, P. (2025). A structured evaluation of LLM-generated step-by-step instructions in cadaveric brachial plexus dissection. BMC Med. Educ., 25.","DOI":"10.1186\/s12909-025-07493-0"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1002\/ase.70120","article-title":"Exploring body donation communication with large language models: Accuracy, readability, and ethical considerations","volume":"18","author":"Ok","year":"2025","journal-title":"Anat. Sci. Educ."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Karampinis, E., Zoumpourli, C.-M., Kontogianni, C., Arkoumanis, T., Koumaki, D., Mantzaris, D., Filippakis, K., Papadopoulou, M.-M., Theofili, M., and Enechukwu, N.A. (2026). Dermatology \u201cAI Babylon\u201d: Cross-language evaluation of AI-crafted dermatology descriptions. Medicina, 62.","DOI":"10.3390\/medicina62010227"}],"container-title":["Children"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-9067\/13\/9\/1272\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T10:09:53Z","timestamp":1789985393000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-9067\/13\/9\/1272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,18]]},"references-count":31,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["children13091272"],"URL":"https:\/\/doi.org\/10.3390\/children13091272","relation":{},"ISSN":["2227-9067"],"issn-type":[{"value":"2227-9067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,18]]}}}