Data augmentation method and system suitable for immune prediction model training process
By acquiring real immune feature data and generating enhanced data using an immune age database, the problem of sample scarcity in the training of immune prediction models was solved, thus improving the training effect of the models.
CN122412945APending Publication Date: 2026-07-17HUAFEI IMMUNOSCIENCE (GUANGDONG) CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUAFEI IMMUNOSCIENCE (GUANGDONG) CO LTD
- Filing Date
- 2026-03-10
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
The lack of samples during the training of existing immune prediction models leads to poor training results.
Method used
By acquiring real immune characteristic data, using an immune age database to identify rare immune characteristic data, and generating enhanced immune characteristic data, high-quality samples are expanded.
Benefits of technology
This effectively expands the training samples for the immune prediction model, improves the model's training performance, and solves the problem of sample scarcity.
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Figure CN122412945A_ABST
Abstract
本申请适用于生物医学的技术领域，提供了一种适用于免疫预测模型训练过程的数据增强方法及其系统，其方法包括先获取多个目标样本对象对应的真实免疫特征数据信息，然后基于免疫年龄数据库信息，根据真实免疫特征数据信息，快速地确定稀有免疫特征数据信息，最后根据稀有免疫特征数据信息，准确地生成增强免疫特征数据信息。本申请能够有助于免疫预测模型的高效训练，促进免疫预测模型在多样化数据上的泛化能力提升，有效扩展并构建出数量充足且质量优异的免疫样本集，为后续的模型优化和免疫年龄预测应用奠定坚实基础。
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