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Utilizing an AI\u2010based platform, the research analysed the expression of CD3, CD5, CD10, CD20, CD23, Cyclin D1, BCL\u20102, BCL\u20106 and Ki\u201067 in 91 samples from 84 patients. The findings demonstrate that, compared to manual interpretation, the AI system provides more objective, reproducible and accurate measurement results. Additionally, this study introduces a virtual dual immunohistochemical labelling technique for simultaneous antigen visualization. Although limited by its single\u2010centre retrospective design, the research establishes a promising AI\u2010assisted framework that enhances the accuracy, standardization and diagnostic efficiency in distinguishing between these two clinically distinct lymphomas.<\/jats:p>","DOI":"10.1111\/bjh.70383","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T21:28:42Z","timestamp":1773005322000},"page":"1287-1295","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An\n                    <scp>AI<\/scp>\n                    \u2010based\n                    <scp>IHC<\/scp>\n                    quantification technique for assisting in the differentiation of\n                    <scp>MCL<\/scp>\n                    from\n                    <scp>CLL<\/scp>\n                    \/\n                    <scp>SLL<\/scp>"],"prefix":"10.1111","volume":"208","author":[{"given":"Zizhu","family":"Tian","sequence":"first","affiliation":[{"name":"Department of Hematology The Second Xiangya Hospital of Central South University  Changsha Hunan P. 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