{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T00:21:25Z","timestamp":1793319685321,"version":"4.5.0"},"reference-count":27,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"4","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose:<\/jats:title>\n                    <jats:p>To compare the diagnostic accuracy and public health utility of Gemini 2.5 Flash and GPT-4 for early childhood caries (ECC) risk triage in classifying presentations as high risk (warranting immediate referral) or low risk (amenable to preventive counseling).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods:<\/jats:title>\n                    <jats:p>A standardized dataset of 50 clinical vignettes (25 high risk and 25 low risk) was evaluated against both large language models via official application programming interfaces using a blinded, prospective comparative design (CONSORT-AI; TRIPOD+AI). This constitutes a vignette-based internal validation study and does not represent a clinical diagnostic accuracy study. Ground truth was established by two consultant pediatric dentists (intraclass correlation coefficient = 0.92). Performance was quantified using sensitivity, specificity, positive predictive value, negative predictive value, and false negative rate (FNR). Readability, actionability, and multilingual competence in Hindi and Tamil were additionally assessed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Both models exceeded the 80% accuracy threshold. GPT-4 achieved significantly higher sensitivity (92.0% vs. 80.0%;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = 0.032) and a lower FNR (8.0% vs. 20.0%), with superior readability (Flesch-Kincaid Grade Level 5.9 vs. 8.1), actionability (4.8 vs. 4.2), and cross-lingual consistency. Both models achieved 100% safety disclaimer compliance in English.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>GPT-4 demonstrates a statistically superior safety profile for ECC risk triage. As a Level 1 adjunct, it can assist pediatric dentists by prescreening caregiver-reported presentations, reducing diagnosis lag, and directing specialist capacity toward confirmed high-risk pathology without replacing clinical judgment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical Relevance:<\/jats:title>\n                    <jats:p>This study establishes that GPT-4 is a safer and more accessible AI triage tool than Gemini 2.5 Flash for pediatric dental screening, particularly in linguistically diverse, resource-constrained settings where specialist access is limited.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/jisppd.jisppd_203_26","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T16:00:26Z","timestamp":1787673626000},"page":"392-398","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":1,"title":["Large language models for early childhood caries risk triage: A validation study using standardized pediatric dental vignettes"],"prefix":"10.4103","volume":"44","author":[{"given":"Balaji","family":"Suresh","sequence":"first","affiliation":[{"name":"Department of Pediatric and Preventive Dentistry, SRM Dental College, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nandini Devi","family":"Madiajagane","sequence":"additional","affiliation":[{"name":"Department of Dentistry, Maa Kauvery Women and Children\u2019s Hospital, Tiruchirappalli, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria Anthonet","family":"Sruthi","sequence":"additional","affiliation":[{"name":"Department of Pedodontics and Preventive Dentistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"R2-20260826","doi-asserted-by":"crossref","first-page":"1624571","DOI":"10.3389\/fdmed.2025.1624571","article-title":"Global, regional and national burden of deciduous dental caries from 1990 to 2021: Analysis of risk factors and prediction of trends in 2035","volume":"6","author":"Yang","year":"2025","journal-title":"Front Dent Med"},{"key":"R3-20260826","doi-asserted-by":"crossref","first-page":"1623666","DOI":"10.3389\/fped.2025.1623666","article-title":"Association between early childhood caries and anthropometric growth and nutritional status in preschool children: A cross-sectional study","volume":"13","author":"Cao","year":"2025","journal-title":"Front Pediatr"},{"key":"R4-20260826","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1186\/s12903-024-04407-2","article-title":"Prevalence and risk indicators of early childhood caries among toddlers in Caloocan City, Philippines: A cross-sectional study","volume":"24","author":"Oliveros-Villarico","year":"2024","journal-title":"BMC Oral Health"},{"key":"R5-20260826","first-page":"16","article-title":"Workforce planning models for oral health care: A scoping review","volume":"7","author":"O'Malley","year":"2022","journal-title":"JDR Clin Trans Res"},{"key":"R6-20260826","first-page":"e83767","article-title":"A review of early childhood caries: Risk factors, management, and policy recommendations","volume":"17","author":"Patel","year":"2025","journal-title":"Cureus"},{"key":"R7-20260826","doi-asserted-by":"crossref","first-page":"2615","DOI":"10.3390\/healthcare13202615","article-title":"Comparative evaluation of responses from ChatGPT-5, Gemini 2.5 flash, Grok 4, and Claude sonnet-4 Chatbots to questions about endodontic iatrogenic events","volume":"13","author":"Ta\u015fy\u00fcrek","year":"2025","journal-title":"Healthcare (Basel)"},{"key":"R8-20260826","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.identj.2024.10.014","article-title":"Large language models in dental licensing examinations: Systematic review and meta-analysis","volume":"75","author":"Liu","year":"2025","journal-title":"Int Dent J"},{"key":"R9-20260826","doi-asserted-by":"crossref","first-page":"307","DOI":"10.3389\/fpubh.2017.00307","article-title":"Sensitivity, specificity, and predictive values: Foundations, pliabilities, and pitfalls in research and practice","volume":"5","author":"Trevethan","year":"2017","journal-title":"Front Public Health"},{"key":"R10-20260826","doi-asserted-by":"crossref","first-page":"e54633","DOI":"10.2196\/54633","article-title":"A reliable and accessible caregiving language model (CaLM) to support tools for caregivers: Development and evaluation study","volume":"8","author":"Parmanto","year":"2024","journal-title":"JMIR Form Res"},{"key":"R11-20260826","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1038\/s41591-020-1037-7","article-title":"SPIRIT-AI and CONSORT-AI Working Group. 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