Fenglong Ma
Biographic Data
| ID | 3801494 |
|---|---|
| NAME | Fenglong Ma |
| GIVEN NAMES | Fenglong |
| FAMILY NAME | Ma |
| SIGNATURE | MA F |
| AFFILIATIONS | The Pennsylvania State University, USA |
| ORCID | 0000-0002-4999-0303 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Supporting physical activity adoption through recommender system technology
We tested the potential for recommender system technology to provide personalized physical activity (PA) suggestions for inactive young adults with high bodyweight. We developed a recommender system using data from the 2017 Behavioral Risk Factor Surveillance System and assessed interest in using the system among 47 young adults (mean age = 23.0 years; 63.4% female; 65.0% White; mean BMI = 29.4). Eleven of these participants (mean age = 23.6 year…
Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces
Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors a…
No prominent works on this page.
Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces
Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors a…
Supporting physical activity adoption through recommender system technology
We tested the potential for recommender system technology to provide personalized physical activity (PA) suggestions for inactive young adults with high bodyweight. We developed a recommender system using data from the 2017 Behavioral Risk Factor Surveillance System and assessed interest in using the system among 47 young adults (mean age = 23.0 years; 63.4% female; 65.0% White; mean BMI = 29.4). Eleven of these participants (mean age = 23.6 year…
Medicine (2 works) · Behavioral Risk Factor Surveillance System (1 work) · Computer Science (1 work) · COVID-19 epidemiological studies (1 work) · Data-Driven Disease Surveillance (1 work) · Environmental health (1 work) · Gerontology (1 work) · Influenza Virus Research Studies (1 work) · Influenza-like illness (1 work) · Mobile Health and mHealth Applications (1 work)