Patent value prediction in biomedical textiles: A method based on a fusion of machine learning models.

ABSTRACT: Patent value prediction is essential for technology innovation management. This study aims to enhance technology innovation management in the field of biomedical textiles by processing complex biomedical patent information to improve the accuracy of predicting patent values. A patent value grading prediction method based on a fusion of machine learning models is proposed, utilizing 113,428 biomedical textile patents as the research sample. The method combines BERT (Bidirectional Encoder Representations from Transformers) and a stacking strategy to classify and predict the value class of biomedical textile patents using both textual information and structured patent features. We implemented this method for patent value prediction in biomedical textiles, leading to the development of BioTexV

SUBMITTER: He Y 

PROVIDER: S-EPMC12021132 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature