Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Yanlong Qiu"'
Publikováno v:
BMC Bioinformatics, Vol 23, Iss S8, Pp 1-16 (2022)
Abstract Background Cardiovascular disease (CVD) is a serious disease that endangers human health and is one of the main causes of death. Therefore, using the patient’s electronic medical record (EMR) to predict CVD automatically has important appl
Externí odkaz:
https://doaj.org/article/f96835708d774d24b25e4b335680353d
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-15 (2021)
Abstract Background Interactions of microbes and diseases are of great importance for biomedical research. However, large-scale of microbe–disease interactions are hidden in the biomedical literature. The structured databases for microbe–disease
Externí odkaz:
https://doaj.org/article/5126382b95f14defa421c0e00f08b7f0
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 20, Iss S3, Pp 1-10 (2020)
Abstract Background Electronic medical records contain a variety of valuable medical information for patients. So, when we are able to recognize and extract risk factors for disease from EMRs of patients with cardiovascular disease (CVD), and are abl
Externí odkaz:
https://doaj.org/article/9a56492b3ccf4f5aac5d5f1fc532f96b
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 4, Pp 2825-2841 (2020)
Clinical event detection (CED) is a hot topic and essential task in medical artificial intelligence, which has attracted the attention from academia and industry over the recent years. However, most studies focus on English clinical narratives. Owing
Externí odkaz:
https://doaj.org/article/febf9c539c834c84aa0b74d2a31ddace
Autor:
Jiacai Yi, Chengkun Wu, Xiaochen Zhang, Xinyi Xiao, Yanlong Qiu, Wentao Zhao, Tingjun Hou, Dongsheng Cao
Publikováno v:
Bioinformatics. 38:4562-4572
Motivation Automatic recognition of chemical structures from molecular images provides an important avenue for the rediscovery of chemicals. Traditional rule-based approaches that rely on expert knowledge and fail to consider all the stylistic variat
Millimeter-wave (mmWave) radars have found applications in a wide range of domains, including human tracking, health monitoring, and autonomous driving, for their unobtrusive nature and high range accuracy. These capabilities, however, if used for ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a27ed0c5af81cb07bf496d1070bee985
http://arxiv.org/abs/2201.03336
http://arxiv.org/abs/2201.03336
Publikováno v:
2021 3rd International Conference on Natural Language Processing (ICNLP).
Medical named entity recognition (NER) is an important task of clinical natural language processing (NLP). It is a hot issue in intelligent medicine research. Recently, the proposed Lattice-LSTM model has demonstrated that incorporating information o
Publikováno v:
BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, Vol 20, Iss S3, Pp 1-10 (2020)
BMC Medical Informatics and Decision Making, Vol 20, Iss S3, Pp 1-10 (2020)
Background Electronic medical records contain a variety of valuable medical information for patients. So, when we are able to recognize and extract risk factors for disease from EMRs of patients with cardiovascular disease (CVD), and are able to use
Background Cardiovascular disease (CVD), as a chronic disease, has been perplexing human beings and is one of the serious diseases endangering life and health. Therefore, using the electronic medical record information of patients to automatically pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::132c7b033d61f4cb6dc4f544a2cfb052
https://doi.org/10.21203/rs.3.rs-31061/v1
https://doi.org/10.21203/rs.3.rs-31061/v1
Publikováno v:
Neural Information Processing ISBN: 9783030638290
ICONIP (1)
ICONIP (1)
Cardiovascular disease (CVD) is one of the serious diseases endangering human life and health. Therefore, using the electronic medical record information to automatically predict CVD has important application value in intelligent auxiliary diagnosis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0427f669d3d49c557ae134597d0d32a3
https://doi.org/10.1007/978-3-030-63830-6_60
https://doi.org/10.1007/978-3-030-63830-6_60