相关论文: Characterizing Diabetes, Diet, Exercise, and Obesi…
Diabetes Mellitus is a metabolic disorder which may result in severe and potentially fatal complications if not well-treated and monitored. In this study, a quantitative analysis of the data collected using CGM (Continuous Glucose…
We propose to analyze the level of recommendation and spreading in the sharing of scientific papers on Twitter to understand the interactions of communities around papers and to develop the "Community of Attention Network" (CAN). In this…
To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider ``quantified self'' movement and…
Personal health devices can enable continuous monitoring of health parameters. However, the benefit of these devices is often directly related to the frequency of use. Therefore, adherence to personal health devices is critical. This paper…
Twitter has been identified as one of the most popular and promising altmetrics data sources, as it possibly reflects a broader use of research articles by the general public. Several factors, such as document age, scientific discipline,…
Over the last decade, exoskeletons have had an extensive impact on different disciplines and application domains such as assisted living, military, healthcare, firefighting, and industries, on account of their diverse and dynamic…
Childhood and adolescent obesity rates are a global concern because obesity is associated with chronic diseases and long-term health risks. Artificial intelligence technology has emerged as a promising solution to accurately predict obesity…
Women with polycystic ovary syndrome (PCOS) face substantially elevated risks of body image distress, disordered eating, and metabolic challenges, yet existing natural language processing approaches for detecting these conditions lack…
Leveraging social media data to understand people's lifestyle choices is an exciting domain to explore but requires a multiview formulation of the data. In this paper, we propose a joint embedding model based on the fusion of neural…
In this paper, models of the blood glucose (BG) dynamics in people with Type 1 diabetes (T1D) in response to moderate intensity aerobic activity are derived from physiology-based first principles and system identification experiments. We…
The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and…
Social media platforms provide convenient means for users to participate in multiple online activities on various contents and create fast widespread interactions. However, this rapidly growing access has also increased the diverse…
In the last decade drug overdose deaths reached staggering proportions in the US. Besides the raw yearly deaths count that is worrisome per se, an alarming picture comes from the steep acceleration of such rate that increased by 21% from…
Diabetes mellitus type II affects around 8 percent of the total adult population in the world. It is the fifth leading cause of death in high income countries and an epidemic in developing countries. We analyze protein-protein interaction…
Social media platforms actively moderate content glorifying harmful behaviors like eating disorders, which include anorexia and bulimia. However, users have adapted to evade moderation by using coded hashtags. Our study investigates the…
Social networks influence health-related behaviors, such as obesity and smoking. While researchers have studied social networks as a driver for diffusion of influences and behaviors, it is less understood how the structure or topology of…
In this study we have investigated the relationship between different document characteristics and the number of Mendeley readership counts, tweets, Facebook posts, mentions in blogs and mainstream media for 1.3 million papers published in…
Social media data allows researchers to construct large digital cohorts to study the interplay between human behavior and medical treatment.Identifying the users most relevant to a specific health problem is, however, a challenge in that…
Objectives To test the feasibility of using Twitter data to assess determinants of consumers' health behavior towards Human papillomavirus (HPV) vaccination informed by the Integrated Behavior Model (IBM). Methods We used three Twitter…
Stress is a nigh-universal human experience, particularly in the online world. While stress can be a motivator, too much stress is associated with many negative health outcomes, making its identification useful across a range of domains.…