A5068698856- Urban Green Space and Health
- Smoking Behavior and Cessation
- Air Quality and Health Impacts
- Physical Activity and Health
- HIV, Drug Use, Sexual Risk
- Leaf Properties and Growth Measurement
- Urban Heat Island Mitigation
- Image Processing Techniques and Applications
- Radioactive element chemistry and processing
- Optical Systems and Laser Technology
- Impact of Technology on Adolescents
- Behavioral Health and Interventions
- Substance Abuse Treatment and Outcomes
- Video Surveillance and Tracking Methods
- Sex work and related issues
- Image and Object Detection Techniques
- Obesity, Physical Activity, Diet
- HIV/AIDS Research and Interventions
- Chemical Synthesis and Characterization
- Nonlinear Dynamics and Pattern Formation
- Exercise and Physiological Responses
- Mechanical and Optical Resonators
- Image Processing and 3D Reconstruction
- Mental Health Research Topics
- Industrial Vision Systems and Defect Detection
University of Michigan
2022-2025
Xidian University
2021-2024
Tsinghua University
2021-2024
Georgetown Lombardi Comprehensive Cancer Center
2022
Georgetown University
2022
Occupational Cancer Research Centre
2022
Xiangtan University
2021
Guangdong Institute of Intelligent Manufacturing
2021
Yale University
2019
East China University of Technology
2019
Multiview clustering aims to leverage information from multiple views improve the performance. Most previous works assumed that each view has complete data. However, in real-world datasets, it is often case a may contain some missing data, resulting problem of incomplete multiview (IMC). Previous approaches this have at least one following drawbacks: 1) employing shallow models, which cannot well handle dependence and discrepancy among different views; 2) ignoring hidden data; 3) being...
Identifying determinants of smoking cessation is critical for developing optimal treatments and interventions. Machine learning (ML) becoming more prevalent success prediction in treatment programs. However, only individuals with an intention to quit cigarettes participate such programs, which limits the generalizability results. This study applies data from Population Assessment Tobacco Health (PATH), a United States longitudinal nationally representative survey, select primary train ML...
Abstract Introduction Cigarette smoking continues to pose a threat public health. Identifying individual risk factors for initiation is essential further mitigate this epidemic. To the best of our knowledge, no study today has used machine learning (ML) techniques automatically uncover informative predictors onset among adults using Population Assessment Tobacco and Health (PATH) study. Aims Methods In work, we employed random forest paired with Recursive Feature Elimination identify...
<title>Abstract</title> Background The association between urban green spaces, especially street greenery, and physical activity (PA) in older adults is understudied. This study utilized Baidu Street View images deep learning techniques to objectively assess greenery exposure its relationship with different types of PA among China. Methods investigated 1326 (aged 60 or above) living Beijing, Physical Activity Scale for the Elderly (PASE) was used level adults. were 500-meter buffer zone...
Abstract Identifying determinants of smoking cessation is critical for developing optimal treatments and interventions. Machine learning (ML) becoming more prevalent success prediction in treatment programs. However, only individuals with an intention to quit participate such programs, which limits the generalizability results. This study applies data from Population Assessment Tobacco Health (PATH), a United States longitudinal nationally representative survey, select primary train ML...
Physical Activity Scale for College Students (IPAQ-SF): A Cross-validation Study in China Tan Jiale, Jun Qiu, Hongjun Yu PURPOSE: To cross-validate validate the International Questionnaire-Short Form (IPAQ-SF) among Chinese college students. METHODS: 166 students (99 males & 67 females; aged 18.61 ± 1.05 yr, Height = 170.36 8.21 cm, Weight 62.20 11.32 kg, BMI 21.37 3.08) students' 7-day energy expenditure (EE) data were estimated using ActiGraph wGT3X-BT accelerometers. They also asked to...
PURPOSE:The purpose of this study was to use deep learning assess the street-level greenery and its association with Chinese adolescents' physical activity sedentary behavior. METHODS:A survey 953 (659 males & 294 females; aged 17.97 ± 0.67, Height = 173.48 8.00 cm, Weight 65.44 13.33 kg, BMI 21.65 3.23) adolescents from different provinces students conducted in September 2021, a buffer zone set up within 800 meters home address. Physical levels were assessed by Harvard Alumni Health Study...
PURPOSE: To estimate the relationship between social networks and energy expenditures (EE) of physical activity (PA) among Chinese College Students. METHODS: We conducted yearly health survey on 3448 (2427 males & 1021 females, Age = 18.27 ± 16.74 yr., Height 173.53 16.24 cm, Weight 64.82 12.56 kg, BMI 22.47 3.33) freshmen from Tsinghua University in 2021. PA was measured by Harvard Alumni Health Study Physical Activity Questionnaire (HAHS-PAQ). Social for students were Sample Egocentric...
PURPOSE: The purpose of this study was to access the association between street greenery and physical activity among Chinese adolescents. METHOD: A questionnaire survey on 798 (564 males & 234 females; aged 17.93 ± 0.62, Height = 173.65 7.87 cm, Weight 65.25 13.54 kg, BMI 21.53 3.73) adolescents performed in September 2021 cross-sectionally, which measures their levels by Harvard Alumni Health Study Physical Activity Questionnaire (HAHS-PAQ). Buffer zones with a radius 800 meters were set...
Abstract Cigarette smoking continues to pose a threat public health. Identifying individual risk factors for initiation is essential further mitigate this epidemic. To our knowledge, no study today has used Machine Learning (ML) techniques automatically uncover informative predictors of onset among adults using the Population Assessment Tobacco and Health (PATH) study. In work, we employed Random Forest paired with Recursive Feature Elimination identify relevant PATH variables that predict...