{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T06:11:16Z","timestamp":1780467076267,"version":"3.54.1"},"reference-count":19,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["acsjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Cytopathology"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Proficiency in cytopathologic diagnosis depends heavily on extensive hands\u2010on practice and immediate error correction. Traditional teaching models, however, are constrained by limited practice opportunities and delayed feedback, which fails to meet the core skill\u2010development needs of residents.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      In total, 45 pathology residents were enrolled and assigned to two groups. The experimental group (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a020) adopted a tripartite\n                      <jats:italic>teacher\u2013artificial intelligence\u2013resident<\/jats:italic>\n                      collaborative teaching model, whereas the control group (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a025) received conventional instruction. Both groups underwent an identical 8\u2010week teaching cycle.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The questionnaire results from the experimental group indicated that 19 of 20 residents (9%) deemed the new model highly necessary, and 15 of 20 (75%) believed it significantly improved their diagnostic competence. Semistructured interviews further revealed that the model enhanced diagnostic ability, facilitated personalized learning, and alleviated learning anxiety. For objective metrics, the experimental group demonstrated a significantly higher postintervention concordance rate for gray\u2010zone cell identification (78.65%) compared with both their preintervention baseline (64.38%) and the contemporaneous control group (66.84%;\n                      <jats:italic>t<\/jats:italic>\n                      \u00a0=\u00a08.962;\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a0.001). In addition, the experimental group exhibited a markedly faster diagnostic speed (mean\u00a0\u00b1\u00a0standard deviation, 3.05\u00a0\u00b1\u00a00.52 minutes per case) compared with their preintervention performance (5.92\u00a0\u00b1\u00a00.85 minutes per case) and the control group (5.63\u00a0\u00b1\u00a00.79 minutes per case;\n                      <jats:italic>t<\/jats:italic>\n                      \u00a0=\u00a014.821;\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a0.001). No statistically significant changes were observed in the control group (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&gt; .05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study demonstrates that artificial intelligence technology integrated with real\u2010time visual interaction effectively improves the cytopathologic diagnostic skills of residents and merits wider promotion in pathology education.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cncy.70097","type":"journal-article","created":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T09:20:39Z","timestamp":1779096039000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Practical exploration of real\u2010time visual interactive artificial intelligence technology in cytopathology education"],"prefix":"10.1002","volume":"134","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3903-0541","authenticated-orcid":false,"given":"Wenhao","family":"Ren","sequence":"first","affiliation":[{"name":"Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology Peking University Cancer Hospital and Institute  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lulu","family":"Rong","sequence":"additional","affiliation":[{"name":"Department of Pathology Beijing Chao\u2010Yang Hospital Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology Peking University Cancer Hospital and Institute  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Pathology Beijing Chao\u2010Yang Hospital Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunhua","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Pathology Yunnan Cancer Hospital  Kunming China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanli","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology Peking University Cancer Hospital and Institute  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Pathology Beijing Chao\u2010Yang Hospital Capital Medical University  Beijing 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