Zobrazeno 1 - 10
of 314
pro vyhledávání: '"Tang, Buzhou"'
This work proposes a novel and simple sequential learning strategy to train models on videos and texts for multimodal sentiment analysis. To estimate sentiment polarities on unseen out-of-distribution data, we introduce a multimodal model that is tra
Externí odkaz:
http://arxiv.org/abs/2409.04473
Autor:
Zong, Hui, Wu, Rongrong, Cha, Jiaxue, Feng, Weizhe, Wu, Erman, Li, Jiakun, Shao, Aibin, Tao, Liang, Li, Zuofeng, Tang, Buzhou, Shen, Bairong
Publikováno v:
Journal of Biomedical Informatics. 2024;157:104716.
Objective: This study aims to review the recent advances in community challenges for biomedical text mining in China. Methods: We collected information of evaluation tasks released in community challenges of biomedical text mining, including task des
Externí odkaz:
http://arxiv.org/abs/2403.04261
Autor:
Zhan, Kecheng, Peng, Weihua, Xiong, Ying, Fu, Huhao, Chen, Qingcai, Wang, Xiaolong, Tang, Buzhou
Publikováno v:
JMIR Medical Informatics, Vol 9, Iss 4, p e23587 (2021)
BackgroundFamily history information, including information on family members, side of the family of family members, living status of family members, and observations of family members, plays an important role in disease diagnosis and treatment. Fami
Externí odkaz:
https://doaj.org/article/b0c3ed4ffe0548f28f08d71505fc452b
Autor:
Liang, Jun, Li, Ying, Zhang, Zhongan, Shen, Dongxia, Xu, Jie, Zheng, Xu, Wang, Tong, Tang, Buzhou, Lei, Jianbo, Zhang, Jiajie
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 2, p e24813 (2021)
BackgroundThe adoption rate of electronic health records (EHRs) in hospitals has become a main index to measure digitalization in medicine in each country. ObjectiveThis study summarizes and shares the experiences with EHR adoption in China and in t
Externí odkaz:
https://doaj.org/article/7ef5898d6f1848718bc0243200f3e17f
Publikováno v:
JMIR Medical Informatics, Vol 8, Iss 12, p e23357 (2020)
BackgroundWith the popularity of electronic health records (EHRs), the quality of health care has been improved. However, there are also some problems caused by EHRs, such as the growing use of copy-and-paste and templates, resulting in EHRs of low q
Externí odkaz:
https://doaj.org/article/7ea6d301ee394ab8b9358d6972b8e7b6
Autor:
Wang, Xiaofeng, Chen, Shuai, Li, Tao, Li, Wanting, Zhou, Yejie, Zheng, Jie, Chen, Qingcai, Yan, Jun, Tang, Buzhou
Publikováno v:
JMIR Medical Informatics, Vol 8, Iss 7, p e17958 (2020)
BackgroundDepression is a serious personal and public mental health problem. Self-reporting is the main method used to diagnose depression and to determine the severity of depression. However, it is not easy to discover patients with depression owing
Externí odkaz:
https://doaj.org/article/840d76bd8a904c9098f1d35f9039b9eb
Autor:
Li, Linfeng, Wang, Peng, Wang, Yao, Wang, Shenghui, Yan, Jun, Jiang, Jinpeng, Tang, Buzhou, Wang, Chengliang, Liu, Yuting
Publikováno v:
JMIR Medical Informatics, Vol 8, Iss 5, p e17645 (2020)
BackgroundKnowledge graph embedding is an effective semantic representation method for entities and relations in knowledge graphs. Several translation-based algorithms, including TransE, TransH, TransR, TransD, and TranSparse, have been proposed to l
Externí odkaz:
https://doaj.org/article/89828163ab1741de9494c702a29c7413
Publikováno v:
JMIR Medical Informatics, Vol 8, Iss 4, p e17622 (2020)
BackgroundDeidentification of clinical records is a critical step before their publication. This is usually treated as a type of sequence labeling task, and ensemble learning is one of the best performing solutions. Under the framework of multi-learn
Externí odkaz:
https://doaj.org/article/41351ce694b645f9b1b581443c03b693
Existing multimodal sentiment analysis tasks are highly rely on the assumption that the training and test sets are complete multimodal data, while this assumption can be difficult to hold: the multimodal data are often incomplete in real-world scenar
Externí odkaz:
http://arxiv.org/abs/2401.13697
Retrieval-based augmentations (RA) incorporating knowledge from an external database into language models have greatly succeeded in various knowledge-intensive (KI) tasks. However, integrating retrievals in non-knowledge-intensive (NKI) tasks is stil
Externí odkaz:
http://arxiv.org/abs/2401.02993