A novel neural network model fusion approach for improving medical named entity recognition in online health expert question-answering services

Author:

Hu ZeORCID,Ma Xiaoning

Funder

Tianjin Municipal Education Commission

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference39 articles.

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2. Bikel, D. M., Miller, S., Schwartz, R., & Weischedel, R. (1997). Nymble: A High-Performance Learning Name-Finder. In Proceedings of the fifth conference on applied natural language processing (pp. 194–201).

3. Chalapathy, R., Borzeshi, E. Z., & Piccardi, M. (2016). Bidirectional LSTM-CRF for Clinical Concept Extraction. In Proceedings of the Clinical Natural Language Processing Workshop (ClinicalNLP) (pp. 7-12).

4. Fine-grained legal entity annotation: A case study on the Brazilian supreme court;Correia;Information Processing & Management,2022

5. Context-sensitive gender inference of named entities in text;Das;Information Processing & Management,2021

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