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Updated: Jun 19, 2026

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques
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在OSCC中NR3C1表达模式的基于变压器的分类和解释性:代谢适应洞察力

Monal Yuwanati1, Pradeep Kumar Yadalam2, Senthilmurugan Mullainathan3

  • 1Department of Oral and Maxillofacial Pathology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600077, India.

Journal of oral biology and craniofacial research
|March 2, 2026
PubMed
概括

变压器模型,特别是RoBERTa,比传统方法显著提高了NR3C1蛋白序列分类的准确性. 这些先进的模型在计算生物学任务中提供了卓越的性能.

关键词:
人工智能诊断的人工智能诊断癌症 癌症 癌症 癌症深度学习是一种深度学习.诊断创新是一种创新.葡萄糖皮质类受体受体变压器模型变压器模型

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