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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Characterizing The Performance And Behaviors Of Runners Using Twitter, Qian He, Emmanuel Agu, Diane Strong, Bengisu Tulu, Peder Pedersen
Characterizing The Performance And Behaviors Of Runners Using Twitter, Qian He, Emmanuel Agu, Diane Strong, Bengisu Tulu, Peder Pedersen
Emmanuel O. Agu
Running is a popular physical activity that improves physical and mental wellbeing. Unfortunately, up-to- date information about runners’ performance and psychological wellbeing is limited. Many questions remain unanswered, such as how far and how fast runners typically run, their preferred running times and frequencies, how long new runners persist before dropping out, and what factors cause runners to quit. Without hard data, establishing patterns of runner behavior and mitigating the challenges they face are difficult. Collecting data manually from large numbers of runners for research studies is costly and time consuming. Emerging Social Networking Services (SNS) and fitness tracking devices …
A Context-Aware Activity Recommendation Smartphone Application To Mitigate Sedentary Lifestyles, Qian He, Emmanuel Agu
A Context-Aware Activity Recommendation Smartphone Application To Mitigate Sedentary Lifestyles, Qian He, Emmanuel Agu
Emmanuel O. Agu
A sedentary lifestyle involves irregular or no physical activity. In this kind of lifestyle, people’s activities do not increase their energy expenditure substantially above resting levels. Long periods of sitting, lying, watching television, playing video games, and using the computer are typical examples. Energy expenditures at 1.0-1.5 Metabolic Equivalent Units (METs) are considered sedentary behaviors. A recent study of sedentary lifestyles found that the length of sedentary times is associated with an increased risk of diabetes, cardiovascular disease, and cardiovascular and all-cause mortality. In this study, we developed a smartphone application called “On11”, which continuously tracks and informs the user …
Improved Cardiovascular Risk Prediction Using Nonparametric Regression And Electronic Health Record Data, Edward Kennedy, Wyndy Wiitala, Rodney Hayward, Jeremy Sussman
Improved Cardiovascular Risk Prediction Using Nonparametric Regression And Electronic Health Record Data, Edward Kennedy, Wyndy Wiitala, Rodney Hayward, Jeremy Sussman
Edward H. Kennedy
Use of the electronic health record (EHR) is expected to increase rapidly in the near future, yet little research exists on whether analyzing internal EHR data using flexible, adaptive statistical methods could improve clinical risk prediction. Extensive implementation of EHR in the Veterans Health Administration provides an opportunity for exploration. Our objective was to compare the performance of various approaches for predicting risk of cerebrovascular and cardiovascular (CCV) death, using traditional risk predictors versus more comprehensive EHR data. Regression methods outperformed the Framingham risk score, even with the same predictors (AUC increased from 71% to 73% and calibration also improved). …