{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T06:00:35Z","timestamp":1785477635364,"version":"3.56.0"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T00:00:00Z","timestamp":1785456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>After diagnosis of high-risk human papillomavirus (HPV) infection, patients often seek guidance on cancer risk, colposcopy, follow-up, treatment, partner management, pregnancy, and anxiety. Large language models (LLMs) are increasingly used for medical consultation, but their response quality and safety in this setting require evaluation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this single-center, expert-rated methodological study, 15 patient-style questions based on common outpatient consultations were submitted to ChatGPT-5.5 Instant and DeepSeek-V3. Each model generated three independent responses per question, yielding 90 artificial intelligence (AI)-generated responses. Five blinded gynecology experts independently evaluated all responses, producing 450 expert-rating records. Accuracy, safety, guideline concordance, completeness, and understandability were rated on a 1\u20135 Likert scale. Experts also assessed major error and potential harm. The primary outcome was the proportion of responses without major error or potential harm.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      ChatGPT-5.5 Instant had higher response-level scores than DeepSeek-V3 for accuracy (mean difference, 0.25; 95% CI, 0.11\u20130.39; FDR-adjusted\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.010), safety (0.27; 0.07\u20130.47;\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.010), completeness (0.22; 0.07\u20130.37;\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.020), and composite score (0.18; 0.04\u20130.31;\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.027). The difference in guideline concordance did not remain significant after multiplicity correction (0.16; \u22120.01 to 0.33; FDR-adjusted\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.057), and understandability was similar. Responses without major error or potential harm occurred in 42\/45 (93.3%; 95% CI, 81.7\u201398.6%) ChatGPT responses and 38\/45 (84.4%; 70.5\u201393.5%) DeepSeek-V3 responses (risk difference, 8.9 percentage points; 95% CI, \u221213.3 to 31.1;\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.344). Exploratory question-level risks were observed in HPV16\/18 positivity, normal cytology, partner management, and pregnancy scenarios.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Both two models demonstrated generally strong performance across the evaluated quality domains. ChatGPT achieved higher ratings in several quality domains, but response-level binary safety differences were imprecise and not statistically significant. Both models require guideline-based clinical oversight.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1915867","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T05:37:37Z","timestamp":1785476257000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation and comparison of large language model responses to patient questions after diagnosis of high-risk human papillomavirus infection: an expert-rated digital patient education study"],"prefix":"10.3389","volume":"14","author":[{"given":"Zhen","family":"Hao","sequence":"first","affiliation":[{"name":"Department of Gynaecology, Wuxi Maternity and Child Health Care Hospital, Affiliated Women\u2019s Hospital of Jiangnan University","place":["Wuxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Gynaecology, Wuxi Maternity and Child Health Care Hospital, Affiliated Women\u2019s Hospital of Jiangnan University","place":["Wuxi, China"]},{"name":"Department of Obstetrics, Gynaecology and Reproductive Science, Faculty of Medical and Health Sciences, The University of Auckland","place":["Auckland, New Zealand"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Gynaecology, Wuxi Maternity and Child Health Care Hospital, Affiliated Women\u2019s Hospital of Jiangnan University","place":["Wuxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Gynaecology, Wuxi Maternity and Child Health Care Hospital, Affiliated Women\u2019s Hospital of Jiangnan University","place":["Wuxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huijian","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Gynaecology, Wuxi Maternity and Child Health Care Hospital, Affiliated Women\u2019s Hospital of Jiangnan University","place":["Wuxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,31]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.placenta.2024.10.069","article-title":"Placental extracellular vesicles promoted cervical tumour tissue undergoing death","volume":"158","author":"Wang","year":"2024","journal-title":"Placenta"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/j.mcna.2022.10.006","article-title":"Cervical Cancer screening","volume":"107","author":"Gavinski","year":"2023","journal-title":"Med Clin North 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