Jiaxue Cui
Biographic Data
| ID | 10016031 |
|---|---|
| NAME | Jiaxue Cui |
| GIVEN NAMES | Jiaxue |
| FAMILY NAME | Cui |
| SIGNATURE | CUI J |
| AFFILIATIONS | Dalian Medical University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Application of machine learning algorithms to identify people with low bone density
Background: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a need to develop a method to identify those at high risk for osteoporosis. Objective: This study aimed to develop a machine learning algorithm to effectively identify people with low bone density, using…
Health status of the population in Naqu, Tibet and its latent class analysis
Background: Through a survey and analysis of the population's present state of health, it is possible to give data support for improving the health status of inhabitants in Naqu, Tibet. Additionally, it is possible to provide specific recommendations for the development of medical and healthcare facilities in Tibet. Methods: The health scores of the participants were based on their responses to the four main sections of the questionnaire: dietary…
No prominent works on this page.
Health status of the population in Naqu, Tibet and its latent class analysis
Background: Through a survey and analysis of the population's present state of health, it is possible to give data support for improving the health status of inhabitants in Naqu, Tibet. Additionally, it is possible to provide specific recommendations for the development of medical and healthcare facilities in Tibet. Methods: The health scores of the participants were based on their responses to the four main sections of the questionnaire: dietary…
Application of machine learning algorithms to identify people with low bone density
Background: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a need to develop a method to identify those at high risk for osteoporosis. Objective: This study aimed to develop a machine learning algorithm to effectively identify people with low bone density, using…
Medicine (2 works) · Algorithm (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare (1 work) · Bone density (1 work) · Bone health and osteoporosis research (1 work) · China's Ethnic Minorities and Relations (1 work) · Computer Science (1 work) · Cross-sectional study (1 work) · Demography (1 work)