Shufang Guo
Biographic Data
| ID | 10027484 |
|---|---|
| NAME | Shufang Guo |
| GIVEN NAMES | Shufang |
| FAMILY NAME | Guo |
| SIGNATURE | GUO S |
| AFFILIATIONS | Beijing University of Chinese Medicine |
| ORCID | 0000-0003-3290-0161 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Machine learning-based analysis and prediction of meteorological factors and urban heatstroke diseases
Introduction: Heatstroke is a serious clinical condition caused by exposure to high temperature and high humidity environment, which leads to a rapid increase of the core temperature of the body to more than 40°C, accompanied by skin burning, consciousness disorders and other organ system damage. This study aims to analyze the effect of meteorological factors on the incidence of heatstroke using machine learning, and to construct a heatstroke for…
Associations between patterns of blood heavy metal exposure and health outcomes: Insights from NHANES 2011–2016
The identified patterns of seven-metal mixtures in NHANES 2011-2016 were robust. Pattern 1 exhibited higher correlations with hypertension, heart disease, and malignancy compared to pattern 2, suggesting an interaction between these metals. Particularly, the identified patterns could offer valuable insights into the management of hypertension in healthy populations
No prominent works on this page.
Machine learning-based analysis and prediction of meteorological factors and urban heatstroke diseases
Introduction: Heatstroke is a serious clinical condition caused by exposure to high temperature and high humidity environment, which leads to a rapid increase of the core temperature of the body to more than 40°C, accompanied by skin burning, consciousness disorders and other organ system damage. This study aims to analyze the effect of meteorological factors on the incidence of heatstroke using machine learning, and to construct a heatstroke for…
Associations between patterns of blood heavy metal exposure and health outcomes: Insights from NHANES 2011–2016
The identified patterns of seven-metal mixtures in NHANES 2011-2016 were robust. Pattern 1 exhibited higher correlations with hypertension, heart disease, and malignancy compared to pattern 2, suggesting an interaction between these metals. Particularly, the identified patterns could offer valuable insights into the management of hypertension in healthy populations
Environmental health (2 works) · Medicine (2 works) · Air Quality and Health Impacts (1 works) · Artificial Intelligence (1 works) · Climate Change and Health Impacts (1 works) · Computer Science (1 works) · Diabetes mellitus (1 works) · Endocrinology (1 works) · Epidemiology (1 works) · Geography (1 works)