This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Machine Learning (1465) Natural Language Processing (692) Innovations and Technology in Cancer Care (423)

Published on in Vol 23, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19689, first published .
Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer Diagnosis Framework

Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer Diagnosis Framework

Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer Diagnosis Framework

Authors of this article:

Honglei Liu1, 2 Author Orcid Image ;   Zhiqiang Zhang1, 2 Author Orcid Image ;   Yan Xu3 Author Orcid Image ;   Ni Wang1, 2 Author Orcid Image ;   Yanqun Huang1, 2 Author Orcid Image ;   Zhenghan Yang3 Author Orcid Image ;   Rui Jiang4 Author Orcid Image ;   Hui Chen1, 2 Author Orcid Image
Article Authors Cited by (39) Tweetations (6) Metrics

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  18. Wan C, Feng W, Ma R, Ma H, Wang J, Huang R, Zhang X, Jing M, Yang H, Yu H, Liu Y. Association between depressive symptoms and diagnosis of diabetes and its complications: A network analysis in electronic health records. Frontiers in Psychiatry 2022;13 View
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  25. Reisinezhad P, Fakhrahmad M. Induction of knowledge, attitude and practice of people toward a pandemic from Twitter: a comprehensive model based on opinion mining. Kybernetes 2023;52(7):2507 View
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