Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Keming Lu"'
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-13 (2023)
Abstract Background Differentiating between Crohn’s disease (CD) and intestinal tuberculosis (ITB) with endoscopy is challenging. We aim to perform more accurate endoscopic diagnosis between CD and ITB by building a trustworthy AI differential diag
Externí odkaz:
https://doaj.org/article/7a32aa46e66a410dbac89e0345c4aa5c
Autor:
Yiling Liu, Muxin Ouyang, Wenjie Peng, Wenyang Zhang, Keming Lu, Yujun He, Xiangyan Zeng, Jie Yuan
Publikováno v:
Behavioral Sciences, Vol 14, Iss 1, p 36 (2024)
Implicit learning refers to the process of unconsciously learning complex knowledge through feedback. Previous studies investigated the influences of different types of feedback (e.g., social and non-social feedback) on implicit learning. This study
Externí odkaz:
https://doaj.org/article/823d9e888c984f01b6b4bb4e86d6c8ed
Publikováno v:
Geophysical Research Letters, Vol 50, Iss 7, Pp n/a-n/a (2023)
Abstract Satellite‐based precipitation estimations provide frequent, large‐scale measurements. Deep learning has recently shown significant potential for improving estimation accuracy. Most studies have employed a two‐stage framework, which is
Externí odkaz:
https://doaj.org/article/4f16796a082743b6a10b8926195234d1
Autor:
Meijun Ou, Wenjie Peng, Wenyang Zhang, Muxin Ouyang, Yiling Liu, Keming Lu, Xiangyan Zeng, Jie Yuan
Publikováno v:
Behavioral Sciences, Vol 13, Iss 12, p 963 (2023)
Implicit learning refers to the fact that people acquire new knowledge (structures or rules) without conscious awareness. Previous studies have shown that implicit learning is affected by feedback. However, few studies have investigated the role of s
Externí odkaz:
https://doaj.org/article/d0e8a681e76d4eb29d853fc7cead1d8c
Autor:
Yuanren Tong, Keming Lu, Yingyun Yang, Ji Li, Yucong Lin, Dong Wu, Aiming Yang, Yue Li, Sheng Yu, Jiaming Qian
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-9 (2020)
Abstract Background Differentiating between ulcerative colitis (UC), Crohn’s disease (CD) and intestinal tuberculosis (ITB) using endoscopy is challenging. We aimed to realize automatic differential diagnosis among these diseases through machine le
Externí odkaz:
https://doaj.org/article/2d3d71b73f404ee48e9fb0b28d4b90f1
Publikováno v:
BCP Business & Management. 38:427-436
Forecasting the volatility of financial derivatives and securities returns has always been the core of financial research. Accurate volatility forecast is integral to financial risk management, which is vital for investors and supervision authorities
Background Differentiating between Crohn’s disease (CD) and intestinal tuberculosis (ITB) with endoscopy is challenging. We aim to perform more accurate endoscopic diagnosis between CD and ITB by building a trustworthy AI differential diagnosis app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e98fda5f9c6da0193da6ffe86288ce0
https://doi.org/10.21203/rs.3.rs-1625845/v1
https://doi.org/10.21203/rs.3.rs-1625845/v1
BACKGROUND Differentiating between Crohn’s disease (CD) and intestinal tuberculosis (ITB) has long been an important and challenging problem in clinical practice. Endoscopy is an essential examination for a timely and accurate diagnosis but the res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a0f13846834659969ee3c85e9ac168c
https://doi.org/10.2196/preprints.33844
https://doi.org/10.2196/preprints.33844
Autor:
Ji Li, Sheng Yu, Keming Lu, Yue Li, Dong Wu, Yucong Lin, Yingyun Yang, Aiming Yang, Yuanren Tong, Jiaming Qian
Publikováno v:
BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-9 (2020)
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-9 (2020)
Background Differentiating between ulcerative colitis (UC), Crohn’s disease (CD) and intestinal tuberculosis (ITB) using endoscopy is challenging. We aimed to realize automatic differential diagnosis among these diseases through machine learning al