Zobrazeno 1 - 10
of 106
pro vyhledávání: '"Jiaxi LIN"'
Publikováno v:
Heliyon, Vol 10, Iss 19, Pp e38920- (2024)
Object: This study aims to evaluate the value of super resolution (SR) technology in augmenting the quality of digestive endoscopic images. Methods: In the retrospective study, we employed two advanced SR models, i.e., SwimIR and ESRGAN. Two discrete
Externí odkaz:
https://doaj.org/article/99bd4ec059fe44b9a3661046557ebc89
Autor:
Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He
Publikováno v:
Frontiers in Endocrinology, Vol 15 (2024)
ObjectiveThe aim of this study was to develop and validate a machine learning-based model to predict the development of impaired fasting glucose (IFG) in middle-aged and older elderly people over a 5-year period using data from a cohort study.Methods
Externí odkaz:
https://doaj.org/article/77f896d1588847c099fc4fff979c49d9
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Limited population-based studies discuss the association between fat mass index (FMI) and the risk of liver diseases. This investigation utilized data from the National Health and Nutrition Examination Survey (NHANES) to examine the linkage
Externí odkaz:
https://doaj.org/article/c671d1083f82479f8a59ec6ac10f16fb
Autor:
Lihe Liu, Jiaxi Lin, Lu Liu, Jingwen Gao, Guoting Xu, Minyue Yin, Xiaolin Liu, Airong Wu, Jinzhou Zhu
Publikováno v:
Digital Health, Vol 10 (2024)
Background Nonalcoholic fatty liver disease (NAFLD) is recognized as one of the most common chronic liver diseases worldwide. This study aims to assess the efficacy of automated machine learning (AutoML) in the identification of NAFLD using a populat
Externí odkaz:
https://doaj.org/article/4163b409fa7548138c36327edbb28efa
Autor:
Minyue Yin, Chao Xu, Jinzhou Zhu, Yuhan Xue, Yijia Zhou, Yu He, Jiaxi Lin, Lu Liu, Jingwen Gao, Xiaolin Liu, Dan Shen, Cuiping Fu
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background Asymptomatic COVID-19 carriers with normal chest computed tomography (CT) scans have perpetuated the ongoing pandemic of this disease. This retrospective study aimed to use automated machine learning (AutoML) to develop a predicti
Externí odkaz:
https://doaj.org/article/2393a71b50814662abaa19b3e6bd915b
Publikováno v:
Journal of International Medical Research, Vol 52 (2024)
Objective Osteoporosis is a systemic bone disease characterized by low bone mass, damaged bone microstructure, increased bone fragility, and susceptibility to fractures. With the rapid development of artificial intelligence, a series of studies have
Externí odkaz:
https://doaj.org/article/42cc811d23c64b4b82a3c91eeb4f192c
Autor:
Chenghao Lu, Lu Liu, Minyue Yin, Jiaxi Lin, Shiqi Zhu, Jingwen Gao, Shuting Qu, Guoting Xu, Lihe Liu, Jinzhou Zhu, Chunfang Xu
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
BackgroundLymph node metastasis (LNM) is considered an essential prognosis factor for adenocarcinoma of the esophagogastric junction (AEG), which also affects the treatment strategies of AEG. We aimed to evaluate automated machine learning (AutoML) a
Externí odkaz:
https://doaj.org/article/bcd6368da2f04daeac48a62c8f2b4048
Publikováno v:
Neural Regeneration Research, Vol 20, Iss 4, Pp 1015-1030 (2025)
Cholesterol is an important component of plasma membranes and participates in many basic life functions, such as the maintenance of cell membrane stability, the synthesis of steroid hormones, and myelination. Cholesterol plays a key role in the estab
Externí odkaz:
https://doaj.org/article/deaa28bd5e1c455b8ff52a938b68c361
Autor:
Jiaxi Lin, Shiqi Zhu, Minyue Yin, Hongchen Xue, Lu Liu, Xiaolin Liu, Lihe Liu, Chunfang Xu, Jinzhou Zhu
Publikováno v:
Heliyon, Vol 10, Iss 4, Pp e26559- (2024)
Background and aim: Standard deep learning methods have been found inadequate in distinguishing between intestinal tuberculosis (ITB) and Crohn's disease (CD), a shortcoming largely attributed to the scarcity of available samples. In light of this li
Externí odkaz:
https://doaj.org/article/b8aa9a1057a54d97b20d371b61bef0fa
Publikováno v:
PLoS ONE, Vol 19, Iss 7, p e0304715 (2024)
To investigate the comorbidity of adolescent depression and Internet gaming disorder (IGD) and their shared and unique cognitive-behavioral factors (i.e., self-esteem, dysfunctional attitudes, hopelessness, and coping), a large-scale school-based sur
Externí odkaz:
https://doaj.org/article/e53d830c47d94eb189082276f70c50cd