Zhaohui Tang
Biographic Data
| ID | 7439748 |
|---|---|
| NAME | Zhaohui Tang |
| GIVEN NAMES | Zhaohui |
| FAMILY NAME | Tang |
| SIGNATURE | TANG Z |
| AFFILIATIONS | Central South University |
| ORCID | 0000-0002-2903-8008 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
STI/HIV risk prediction model development—A novel use of public data to forecast STIs/HIV risk for men who have sex with men
A novel automatic framework is proposed for global sexually transmissible infections (STIs) and HIV risk prediction. Four machine learning methods, namely, Gradient Boosting Machine (GBM), Random Forest (RF), XG Boost, and Ensemble learning GBM-RF-XG Boost are applied and evaluated on the Demographic and Health Surveys Program (DHSP), with thirteen features ultimately selected as the most predictive features. Classification and generalization exp…
The escalating burden of cyclist road injuries among reproductive-aged women in china: A longitudinal and gender-specific analysis of the global burden of disease study 1990–2021
China's cycling safety crisis constitutes a demographic emergency, with women facing catastrophic mortality due to infrastructural abandonment, regulatory neglect, and unmitigated micro-mobility risks. Urgent gender-responsive interventions-mandating segregated lanes, enforcing WHO-aligned bicycle legislation (helmets, lighting), and integrating bone health into occupational safety-are essential to avert 81,000 projected disability life-years los…
Machine learning with the body roundness index and associated indicators: A new approach to predicting metabolic syndrome
The combination of BRI and machine learning provides a non-invasive and effective method for predicting MetS and offers a promising strategy for its early prevention. Machine learning models demonstrate significant advantages over baseline rule-based models in terms of sensitivity and predictive performance
Etiology Exploration of Non-alcoholic Fatty Liver Disease From Traditional Chinese Medicine Constitution Perspective: A Cross-Sectional Study
Background: From the traditional Chinese medicine (TCM) constitution theory perspective, the phlegm-dampness constitution is thought to be closely related to the occurrence of non-alcoholic fatty liver disease (NAFLD). However, this viewpoint still lacks rigorous statistical evidence. This study aimed to test the association between the phlegm-dampness constitution and NAFLD. Methods: We conducted a cross-sectional study. Participants were reside…
No prominent works on this page.
Etiology Exploration of Non-alcoholic Fatty Liver Disease From Traditional Chinese Medicine Constitution Perspective: A Cross-Sectional Study
Background: From the traditional Chinese medicine (TCM) constitution theory perspective, the phlegm-dampness constitution is thought to be closely related to the occurrence of non-alcoholic fatty liver disease (NAFLD). However, this viewpoint still lacks rigorous statistical evidence. This study aimed to test the association between the phlegm-dampness constitution and NAFLD. Methods: We conducted a cross-sectional study. Participants were reside…
STI/HIV risk prediction model development—A novel use of public data to forecast STIs/HIV risk for men who have sex with men
A novel automatic framework is proposed for global sexually transmissible infections (STIs) and HIV risk prediction. Four machine learning methods, namely, Gradient Boosting Machine (GBM), Random Forest (RF), XG Boost, and Ensemble learning GBM-RF-XG Boost are applied and evaluated on the Demographic and Health Surveys Program (DHSP), with thirteen features ultimately selected as the most predictive features. Classification and generalization exp…
The escalating burden of cyclist road injuries among reproductive-aged women in china: A longitudinal and gender-specific analysis of the global burden of disease study 1990–2021
China's cycling safety crisis constitutes a demographic emergency, with women facing catastrophic mortality due to infrastructural abandonment, regulatory neglect, and unmitigated micro-mobility risks. Urgent gender-responsive interventions-mandating segregated lanes, enforcing WHO-aligned bicycle legislation (helmets, lighting), and integrating bone health into occupational safety-are essential to avert 81,000 projected disability life-years los…
Machine learning with the body roundness index and associated indicators: A new approach to predicting metabolic syndrome
The combination of BRI and machine learning provides a non-invasive and effective method for predicting MetS and offers a promising strategy for its early prevention. Machine learning models demonstrate significant advantages over baseline rule-based models in terms of sensitivity and predictive performance
Internal Medicine (3 works) · Medicine (3 works) · Biostatistics (2 works) · Body mass index (2 works) · Pathology (2 works) · Public health (2 works) · Alternative medicine (1 works) · Area under curve (1 works) · Artificial Intelligence (1 works) · Burden of disease (1 works)