To improve medical research on chronic diseases, engineers at Ben Gurion University of the Negev (BGU) have developed a method that can help identify chronically ill patients and learn more about their symptoms, treatments and everyday life. analyzes medical-themed social media posts for
The project began with PhD student Maya Stemmer’s insight that big data analysis of millions of self-reported medical terms could provide actionable insights into the symptoms, treatments and daily lives of chronic patients.
Although vast amounts of health-related data are posted daily on Twitter and other networking platforms designed to share information and provide social support, the use of social media data to understand chronic conditions and patient lifestyles is limited to date research.
Maya Stemmer, PhD student at Ben Gurion University. Photo by Pablo Arkoshin
In the first phase of the course, Stemer is a professor in the BGU’s industrial engineering department. Gilad Ravid and Prof. Supervised by Israel Parmet, they combined social network analysis and natural language processing to automatically categorize comments on social media posted by those affected. specific disease.
The engineers looked at tweets from people with inflammatory bowel diseases like Crohn’s disease and ulcerative colitis. They were able to find chronically ill patients who reported frequently about their complaints.
By analyzing the data, the researchers identified distinctive features of Crohn’s disease that helped distinguish it from ulcerative colitis. They were also able to confirm existing information about foods that increase or decrease inflammation.
Another study aims to promote the well-being of people with IBD by examining the potential of Twitter data to access crowd-sourced knowledge about healthy lifestyles.
“We wanted to use posts that describe patients’ daily activities and their impact on their well-being to illustrate lifestyle-related therapies,” Steimer said.
While the methodology used in the study can be modified for other platforms and other diseases, Twitter has the advantage that its API allows academic researchers extended programmatic access.
“Using profiling to identify more patients and collect more data could shed light on strategies for patients to manage their disease and its impact on their quality of life,” Stemmer said.
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