AI Medical Compendium Topic:
Social Media

Clear Filters Showing 421 to 430 of 443 articles

AI opens new frontier for suicide prevention.

CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne

Mining e-cigarette adverse events in social media using Bi-LSTM recurrent neural network with word embedding representation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Recent years have seen increased worldwide popularity of e-cigarette use. However, the risks of e-cigarettes are underexamined. Most e-cigarette adverse event studies have achieved low detection rates due to limited subject sample sizes in...

Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer's Disease Stigma on Twitter.

The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We describe our development of a semi-automated text coding method and use a content analysis of Alzheimer...

Learning about individuals' health from aggregate data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
There is growing awareness that user-generated social media content contains valuable health-related information and is more convenient to collect than typical health data. For example, Twitter has been employed to predict aggregate-level outcomes, s...

Identifying personal health experience tweets with deep neural networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Twitter, as a social media platform, has become an increasingly useful data source for health surveillance studies, and personal health experiences shared on Twitter provide valuable information to the surveillance. Twitter data are known for their i...

Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Soc...