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A total of 6 result was found. Results that relate to HAN Zheng

Advances in the study of biological agents in the treatment of Crohn’s disease

Published on New Medicine 2021,31(1):447-454.
18930 times 5408 times

Han-Han ZHENG Xue-Liang JIANG

Crohn’s disease Biological agents Treatment
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Construction of the risk predition model of mild cognitive impairment in hospitalized elder patients

Published on New Medicine 2024,34(1):14-24.
10394 times 2620 times

WU Ruikai MA Long ZHOU Xiaohui HAN Zhengfeng

Mild cognitive impairment Multivariate Logistic regression model Decision tree model Neural network model Prediction model Elderly
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Analysis of spatial distribution characteristics and influencing factors of depression among elderly people in China

Published on New Medicine 2025,35(3):245-255.
16230 times 3031 times

TANG Yuxuan HAN Zhengfeng

Elderly people Depression Spatial distribution characteristics Influencing factors
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Analysis and trend prediction of the disease burden of atrial fibrillation and flutter in China from 1990 to 2021

Published on New Medicine 2025,35(8):892-902.
8989 times 1587 times

HUO Wenxia MA Yan WU Ruikai HAN Zhengfeng

Atrial fibrillation and flutter Age-period-cohort model Prediction Global disease burden Autoregressive integrated moving average model
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Effect of regulating miR-29b-3p/FoxO3 axis by asiaticoside on alleviating liver injury in rats with non-alcoholic fatty liver disease

Published on New Medicine 2025,35(10):1165-1172.
5355 times 1083 times

TAN Jie LIU Meng TIAN Xia HAN Zheng ZHU Qingxi ZHAN Ting CHEN Mingtao CHEN Aifang HUANG Min

Asiaticoside Non-alcoholic fatty liver disease Liver injury MicroRNA-29b-3p/forkhead box O3
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Constructing a depression risk prediction model for elderly people with activities of daily living impairment based on machine learning algorithms

Published on New Medicine 2026,36(1):37-46.
5592 times 844 times

HUANG Siying MA Yan ZHANG Yuan WU Ruikai HAN Zhengfeng

Activity of daily living ability Depression Risk prediction model Machine learning SHAP algorithm
Details