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Social Media

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Artificial Intelligence and Radiology: A Social Media Perspective.

Current problems in diagnostic radiology
OBJECTIVE: To use Twitter to characterize public perspectives regarding artificial intelligence (AI) and radiology.

Extracting psychiatric stressors for suicide from social media using deep learning.

BMC medical informatics and decision making
BACKGROUND: Suicide has been one of the leading causes of deaths in the United States. One major cause of suicide is psychiatric stressors. The detection of psychiatric stressors in an at risk population will facilitate the early prevention of suicid...

Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models.

Journal of medical Internet research
BACKGROUND: Timely understanding of public perceptions allows public health agencies to provide up-to-date responses to health crises such as infectious diseases outbreaks. Social media such as Twitter provide an unprecedented way for the prompt asse...

Identifying tweets of personal health experience through word embedding and LSTM neural network.

BMC bioinformatics
BACKGROUND: As Twitter has become an active data source for health surveillance research, it is important that efficient and effective methods are developed to identify tweets related to personal health experience. Conventional classification algorit...

Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction mention extraction.

BMC bioinformatics
BACKGROUND: Social media is a useful platform to share health-related information due to its vast reach. This makes it a good candidate for public-health monitoring tasks, specifically for pharmacovigilance. We study the problem of extraction of Adve...

Medical concept normalization in social media posts with recurrent neural networks.

Journal of biomedical informatics
Text mining of scientific libraries and social media has already proven itself as a reliable tool for drug repurposing and hypothesis generation. The task of mapping a disease mention to a concept in a controlled vocabulary, typically to the standard...

Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access.

Journal of medical Internet research
BACKGROUND: On December 6 and 7, 2017, the US Department of Health and Human Services (HHS) hosted its first Code-a-Thon event aimed at leveraging technology and data-driven solutions to help combat the opioid epidemic. The authors—an interdisciplina...

Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm.

PloS one
Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis c...

Understanding the Patterns of Health Information Dissemination on Social Media during the Zika Outbreak.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social media are important platforms for risk communication during public health crises. Effective dissemination of accurate, relevant, and up-to-date health information is important for the public to raise awareness and develop risk management strat...

Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extraction of ADR information can be crucial for healthcare providers, drug manufacturers, and consumers. ...