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Titlebook: Health Information Processing; 9th China Health Inf Hua Xu,Qingcai Chen,Zhengxing Huang Conference proceedings 2024 The Editor(s) (if appli

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Kunli Shi,Gongchi Chen,Jinghang Gu,Longhua Qian,Guodong Zhou theory is described and may be viewed as an extension of the one initially designed by G. Dowek, T. Hardin and C. Kirchner for performing unification of simply typed λ-terms in a first-order setting via the λσ-calculus of explicit substitutions. Additional rules are used to deal with the interaction between E and λσ.
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A Simple but Useful Multi-corpus Transferring Method for Biomedical Named Entity Recognition the current methods and improve its performance. Our method provides a potential solution for biomedical NER enhancement from data perspective, and it could further improve biomedical information extraction with the help of increasingly public available corpus.
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A BART-Based Study of Entity-Relationship Extraction for Electronic Medical Records of CardiovasculaCMeIE. The experimental results demonstrate the effectiveness of both models. Compared to the state-of-the-art baseline model, Cas-CLN, JREwBART achieved an improvement of ., ., and . in terms of F1 score on the three datasets, respectively. PRE-BARTaBT showed F1 score improvements of ., ., and . on the same datasets, respectively.
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Multi-head Attention and Graph Convolutional Networks with Regularized Dropout for Biomedical Relatitext, and finally R-Drop regularization method to enhance network performance. Extensive results on a medical corpus extracted from PubMed show that our model achieves better performance than existing methods.
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y successful proofs often return information that suggests what to try next. The theoretical framework makes extensive use of general algebra, and main results include an extension of many-sorted equational logic to universal quantification over functions, some techniques for handling first order lo
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