A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques
Nowadays, the development of new computer-based technologies has led to rapid increase
in the volume of user-generated textual content on the website. Patient-written medical and …
in the volume of user-generated textual content on the website. Patient-written medical and …
Semi-supervised approach to monitoring clinical depressive symptoms in social media
With the rise of social media, millions of people are routinely expressing their moods,
feelings, and daily struggles with mental health issues on social media platforms like Twitter …
feelings, and daily struggles with mental health issues on social media platforms like Twitter …
Challenges of sentiment analysis for dynamic events
Efforts to assess people's sentiments on Twitter have suggested that Twitter could be a
valuable resource for studying political sentiment and that it reflects the offline political …
valuable resource for studying political sentiment and that it reflects the offline political …
Multimodal mental health analysis in social media
Depression is a major public health concern in the US and globally. While successful early
identification and treatment can lead to many positive health and behavioral outcomes …
identification and treatment can lead to many positive health and behavioral outcomes …
Sentiment analysis of social media posts on pharmacotherapy: A scoping review
C Sharma, S Whittle, PD Haghighi… - Pharmacology …, 2020 - Wiley Online Library
Social media is playing an increasingly central role in patient's decision‐making process.
Advances in technology have enabled meaningful interpretation of discussions on social …
Advances in technology have enabled meaningful interpretation of discussions on social …
Artificial neural network and latent semantic analysis for adverse drug reaction detection
Adverse drug reactions (ADR) are important information for verifying the view of the patient
on a particular drug. Regular user comments and reviews have been considered during the …
on a particular drug. Regular user comments and reviews have been considered during the …
[PDF][PDF] Adverse drug reaction detection using latent semantic analysis
Detecting Adverse Drug Reactions (ADRs) is one of the important information for
determining the view of the patient on one drug. Most studies have investigated the …
determining the view of the patient on one drug. Most studies have investigated the …
An ensemble model for detection of adverse drug reactions
The detection of adverse drug reactions (ADRs) plays a necessary role in comprehending
the safety and benefit profiles of medicines. Although spontaneous reporting stays the …
the safety and benefit profiles of medicines. Although spontaneous reporting stays the …
Improving classification of adverse drug reactions through using sentiment analysis and transfer learning
H Alhuzali, S Ananiadou - … of the 18th BioNLP Workshop and …, 2019 - aclanthology.org
The availability of large-scale and real-time data on social media has motivated research
into adverse drug reactions (ADRs). ADR classification helps to identify negative effects of …
into adverse drug reactions (ADRs). ADR classification helps to identify negative effects of …
Mental health analysis via social media data
AH Yazdavar, MS Mahdavinejad… - 2018 IEEE …, 2018 - ieeexplore.ieee.org
With ubiquity of social media platforms, millions of people are routinely sharing their moods,
feelings and even their daily struggles with mental health issues by expressing it verbally or …
feelings and even their daily struggles with mental health issues by expressing it verbally or …