AIMC Topic: Social Media
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Forecasting influenza-like illness dynamics for military populations using neural networks and social media.
PloS one
Dec 15, 2017
This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of histo...
Critical dynamics in population vaccinating behavior.
Proceedings of the National Academy of Sciences of the United States of America
Dec 11, 2017
Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such s...
SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.
Artificial intelligence in medicine
Oct 27, 2017
With the development of Web 2.0 technology, social media websites have become lucrative but under-explored data sources for extracting adverse drug events (ADEs), which is a serious health problem. Besides ADE, other semantic relation types (e.g., dr...
A descriptive statistical analysis of volume, visibility and attitudes regarding nursing and care robots in social media.
Contemporary nurse
Oct 15, 2017
BACKGROUND: Technology in the healthcare sector is undergoing rapid development. One of the most prominent areas of healthcare in which robots are implemented is nursing homes. However, nursing and technology are often considered as being contradicto...
Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data.
Journal of medical Internet research
Sep 12, 2017
BACKGROUND: Uptake of medicinal drugs (preventive or treatment) is among the approaches used to control disease outbreaks, and therefore, it is of vital importance to be aware of the counts or frequencies of most commonly used drugs and trending topi...
Capturing the Patient's Perspective: a Review of Advances in Natural Language Processing of Health-Related Text.
Yearbook of medical informatics
Sep 11, 2017
Natural Language Processing (NLP) methods are increasingly being utilized to mine knowledge from unstructured health-related texts. Recent advances in noisy text processing techniques are enabling researchers and medical domain experts to go beyond ...
Twitter discussions about the predicaments of robots in geriatric nursing: forecast of nursing robotics in aged care.
Contemporary nurse
Aug 17, 2017
BACKGROUND: People use social media to express perceptions, attitudes and a wide range of concerns regarding human life.
A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals.
Journal of medical Internet research
Aug 14, 2017
BACKGROUND: Linguistic analysis of publicly available Twitter feeds have achieved success in differentiating individuals who self-disclose online as having schizophrenia from healthy controls. To date, limited efforts have included expert input to ev...
Automatic identification of high impact articles in PubMed to support clinical decision making.
Journal of biomedical informatics
Jul 26, 2017
OBJECTIVES: The practice of evidence-based medicine involves integrating the latest best available evidence into patient care decisions. Yet, critical barriers exist for clinicians' retrieval of evidence that is relevant for a particular patient from...
Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals.
Journal of medical Internet research
Jul 24, 2017
BACKGROUND: Social networking services (SNSs) contain abundant information about the feelings, thoughts, interests, and patterns of behavior of adolescents that can be obtained by analyzing SNS postings. An ontology that expresses the shared concepts...
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