(Please note that the room and time differs from regular CLIP colloquium.)
Increasingly, individuals are turning to social media and online forums such as X (formerly Twitter) and Reddit to communicate about a range of issues including their health and well-being, and public health concerns. These user generated social media data are prone to noise. Developing and applying Artificial Intelligence (AI) algorithms can enable researchers to glean pertinent information from social media and online forums for a range of uses. For example, patients’ social media data may include information about their lifestyle that might not typically be reported to clinicians; however, this information may allow clinicians to provide individualized recommendations for managing their patients’ health.
In this talk, I will discuss my work in using AI algorithms with data from various sources (social media, online forums, electronic medical records, and electronic medical records + social media) to gain insights about the health and well-being of individuals. I will also discuss work in which my team and I use survey data to study the expression of anxiety among faculty members in academic institutions in the United States.
Anietie Andy is an Assistant Professor in the Electrical Engineering and Computer Science Department at Howard University. His research interest in the intersection of natural language processing, machine learning, medicine, healthcare, and public health. He develops natural language processing and machine learning algorithms to: (a) predict patients risk for health conditions using data from electronic medical records, social media, and a combination of these sources (b) gain insights about how individuals communicate about health and well-being on social media and the social support needs they express on these platforms