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CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images.

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Title: CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images.
Authors: Zhang, Tianjiao1, Wan, Long1, Zhang, Hongfei1, Zhao, Zhongqian1, Cui, Haijie2, Ma, Jianli2
Source: Briefings in Bioinformatics; May2026, Vol. 27 Issue 3, p1-11, 11p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 195128749
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images.
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  Data: <searchLink fieldCode="JN" term="%22Briefings+in+Bioinformatics%22">Briefings in Bioinformatics</searchLink>; May2026, Vol. 27 Issue 3, p1-11, 11p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=195128749
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        Value: 10.1093/bib/bbag341
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      – Code: eng
        Text: English
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        PageCount: 11
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      – TitleFull: CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images.
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            NameFull: Zhang, Tianjiao
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            NameFull: Wan, Long
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            NameFull: Zhang, Hongfei
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            NameFull: Zhao, Zhongqian
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            – D: 01
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              Text: May2026
              Type: published
              Y: 2026
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