Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Jintao QU"'
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background Most Chinese joint entity and relation extraction tasks in medicine involve numerous nested entities, overlapping relations, and other challenging extraction issues. In response to these problems, some traditional methods decompos
Externí odkaz:
https://doaj.org/article/b408a8ab36db421c96e0f5becadccedc
Publikováno v:
Kafkas Universitesi Veteriner Fakültesi Dergisi, Vol 28, Iss 2, Pp 177-184 (2022)
Th is study examined the eff ects of four levels of rumen-protected methionine (RPM) on the milk performance of dairy goats subjected to severe heat stress (temperature humidity index >90). Seventy-five Guanzhong dairy goats (52.6±4.9 kg) with the s
Externí odkaz:
https://doaj.org/article/85807038f8364d15b0cd60ded45592d0
Autor:
Haoqiang Yu1, Jintao Qu1, Xin Guo1, Li Li1, Xiaofang Zhang1, Qingqing Yang1, Yanli Lu1, Wanchen Li1, Fengling Fu1
Publikováno v:
Journal of Agronomy & Crop Science. Oct2022, Vol. 208 Issue 5, p633-644. 12p.
Background: Most Chinese joint entity and relation extraction tasks in medicine involve numerous nested entities, overlapping relations, and other challenging extraction issues. In response to these problems, some traditional methods decompose the jo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77cfe82d52ebac909bcfbf93c3e6dc36
https://doi.org/10.21203/rs.3.rs-2313192/v1
https://doi.org/10.21203/rs.3.rs-2313192/v1
Autor:
Jintao Qu, Li Li, Yanli Lu, Fengling Fu, Wanchen Li, Guo Xin, Haoqiang Yu, Xiaofang Zhang, Qingqing Yang
Publikováno v:
Journal of Agronomy and Crop Science. 208:633-644
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2ea385bdcb32e02d38d6e17e80e5124
https://doi.org/10.1111/jac.12504
https://doi.org/10.1111/jac.12504
Publikováno v:
Evidence-Based Complementary and Alternative Medicine.
Cerebral palsy is one of the most prevalent neurological disorders and the most frequent cause of disability. Identifying the syndrome by patients’ symptoms is the key to traditional Chinese medicine (TCM) cerebral palsy treatment. Artificial intel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13f3716cfdefde3b25411c863fc1dd88
Publikováno v:
Evidence-Based Complementary and Alternative Medicine.
Traditional clinical named entity recognition methods fail to balance the effectiveness of feature extraction of unstructured text and the complexity of neural network models. We propose a model based on ALBERT and a multihead attention (MHA) mechani
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01ffe620b68208407051902700dd8a18
Publikováno v:
Kafkas Universitesi Veteriner Fakultesi Dergisi.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e83b601f7870475acb4fc1e322b93a8e
https://doi.org/10.9775/kvfd.2021.26647
https://doi.org/10.9775/kvfd.2021.26647
Autor:
Xiaohui Cui, Jintao Qu
Publikováno v:
Journal of Physics: Conference Series. 1651:012116
Based on the automatic machine learning framework, combined with the characteristics of forest fire meteorological data and the adaptive requirements of forest fire prediction, this paper optimizes the data preprocessing, parameter learning, loss fun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24188f6238aabef17c28f67f66845165
https://doi.org/10.1088/1742-6596/1651/1/012116
https://doi.org/10.1088/1742-6596/1651/1/012116
Publikováno v:
Journal of Physics: Conference Series. 1682:012067
Pattern Sequence-based Forecasting (PSF) is an effective method for time series prediction. However, the accuracy of this method depends on the selection of parameters such as the length of the pattern sequence and the number of clusters. In diverse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90205e1615314f524fa9ed4037ba878d
https://doi.org/10.1088/1742-6596/1682/1/012067
https://doi.org/10.1088/1742-6596/1682/1/012067