Gehong Zhang
Biographic Data
| ID | 3930484 |
|---|---|
| NAME | Gehong Zhang |
| GIVEN NAMES | Gehong |
| FAMILY NAME | Zhang |
| SIGNATURE | ZHANG G |
| AFFILIATIONS | Shanxi Medical University |
| ORCID | 0000-0003-0556-8650 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 1 |
Spatiotemporal matching between medical resources and population ageing in China from 2008 to 2017
The spatial and temporal matching degrees between the PAR and NMRTR in mainland China were generally very low. The provincial regions with high PAR largely experienced relatively low spatial matching levels between the PAR and NMRTR, and vice versa. The geographical pattern of the temporal matching between the PAR and NMRTR exhibited the feature of north-south differentiation
Spatiotemporal trends and influence factors of global diabetes prevalence in recent years
Exploring Spatial Trends and Influencing Factors for Gastric Cancer Based on Bayesian Statistics: A Case Study of Shanxi, China
Gastric cancer (GC) is the fourth most common type of cancer and the second leading cause of cancer-related deaths worldwide. To detect the spatial trends of GC risk based on hospital-diagnosed patients, this study presented a selection probability model and integrated it into the Bayesian spatial statistical model. Then, the spatial pattern of GC risk in Shanxi Province in north central China was estimated. In addition, factors influencing GC we…
Exploring Spatial Trends and Influencing Factors for Gastric Cancer Based on Bayesian Statistics: A Case Study of Shanxi, China
Gastric cancer (GC) is the fourth most common type of cancer and the second leading cause of cancer-related deaths worldwide. To detect the spatial trends of GC risk based on hospital-diagnosed patients, this study presented a selection probability model and integrated it into the Bayesian spatial statistical model. Then, the spatial pattern of GC risk in Shanxi Province in north central China was estimated. In addition, factors influencing GC we…
Spatiotemporal matching between medical resources and population ageing in China from 2008 to 2017
The spatial and temporal matching degrees between the PAR and NMRTR in mainland China were generally very low. The provincial regions with high PAR largely experienced relatively low spatial matching levels between the PAR and NMRTR, and vice versa. The geographical pattern of the temporal matching between the PAR and NMRTR exhibited the feature of north-south differentiation
Spatiotemporal trends and influence factors of global diabetes prevalence in recent years
Environmental health (3 works) · Geography (3 works) · Medicine (3 works) · Population (3 works) · Epidemiology (2 works) · Internal Medicine (2 works) · Per capita (2 works) · Ageing (1 works) · Air Quality and Health Impacts (1 works) · Artificial Intelligence (1 works)