Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Yinlin Cheng"'
Autor:
Weidong Ji, Yinlin Cheng, Shengsheng Tang, Kuiying Gu, Huipeng Liao, Lin Li, Yushan Wang, Bo-Yi Yang, Yi Zhou
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 272, Iss , Pp 116109- (2024)
Ambient air pollutants exposures may lead to aggravated Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD). However, there is still a scarcity of empirical studies that have rigorously estimated this association, especially in regions where
Externí odkaz:
https://doaj.org/article/98825dd648a84b1987c9fa9a8688eb97
Publikováno v:
Diabetology & Metabolic Syndrome, Vol 15, Iss 1, Pp 1-12 (2023)
Abstract Objective Diabetes mellitus is a global epidemic disease. Long-time exposure of patients to hyperglycemia can lead to various type of chronic tissue damage. Early diagnosis of and screening for diabetes are crucial to population health. Meth
Externí odkaz:
https://doaj.org/article/a12b3235707e40bd9333d3cd0468868a
Severer air pollution, poorer cognitive function: Findings from 176,345 elders in Northwestern China
Autor:
Zhaohuan Gui, Weidong Ji, Yushan Wang, Jiaxin Li, Yinlin Cheng, Lin Li, Guanghui Dong, Boyi Yang, Yi Zhou
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 271, Iss , Pp 116008- (2024)
Background: Limited evidence exists regarding the link between air pollution exposure and cognitive function in developing countries, particularly in areas with abundant natural sources of particulate matter. Objectives: To investigate this associati
Externí odkaz:
https://doaj.org/article/74ae3331e9fb4288a2d706235cbe4534
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 9 (2022)
ObjectiveTo develop an optimal screening model to identify the individuals with a high risk of hypertension in China by comparing tree-based machine learning models, such as classification and regression tree, random forest, adaboost with a decision
Externí odkaz:
https://doaj.org/article/d442790a6fd246f1a92fd9fde67af18d
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss S2, Pp 1-13 (2021)
Abstract Background Epilepsy is one of the diseases of the nervous system, which has a large population in the world. Traditional diagnosis methods mostly depended on the professional neurologists’ reading of the electroencephalogram (EEG), which w
Externí odkaz:
https://doaj.org/article/a367cc7a97e2469b8442127fc75b9e90
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss S2, Pp 1-9 (2021)
Abstract Background Diabetic Retinopathy (DR) is the most common and serious microvascular complication in the diabetic population. Using computer-aided diagnosis from the fundus images has become a method of detecting retinal diseases, but the detec
Externí odkaz:
https://doaj.org/article/0058d927845f4434af4cb469a5a2e718
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss S2, Pp 1-11 (2021)
Abstract Background Epilepsy was defined as an abnormal brain network model disease in the latest definition. From a microscopic perspective, it is also particularly important to observe the Mutual Information (MI) of the whole brain network based on
Externí odkaz:
https://doaj.org/article/d30f18ec3c174310aa23a69f061904dc
Publikováno v:
IEEE Access, Vol 9, Pp 79600-79610 (2021)
Epilepsy is one of the world’s most common neurological diseases. Reliable early prediction and warning of seizures can provide timely treatment for patients with epilepsy, and improve their quality of life. Compared with most hand-designed predict
Externí odkaz:
https://doaj.org/article/42803457f8124db898f9d675cd0f164e
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 4, Pp 3088-3108 (2020)
The segmentation of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper proposes a new architecture of the U-Net network for retinal blood vessel segmentation. Adding dense block to U-N
Externí odkaz:
https://doaj.org/article/3e019ddc076b4c429e69eeebf726040a
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 27:900-911
Accurate early prediction of epileptic seizures can provide timely treatment for patients. Previous studies have mainly focused on a single temporal or spatial dimension, making it difficult to take both relationships into account. Therefore, the eff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fc94cfbaee2774647b878bccbd6a7ec
https://doi.org/10.1109/jbhi.2022.3221211
https://doi.org/10.1109/jbhi.2022.3221211