A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques

ME Basiri, M Abdar, MA Cifci, S Nemati… - Knowledge-Based …, 2020 - Elsevier
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 …

Semi-supervised approach to monitoring clinical depressive symptoms in social media

AH Yazdavar, HS Al-Olimat, M Ebrahimi… - Proceedings of the …, 2017 - dl.acm.org
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 …

Challenges of sentiment analysis for dynamic events

M Ebrahimi, AH Yazdavar, A Sheth - IEEE Intelligent Systems, 2017 - ieeexplore.ieee.org
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 …

Multimodal mental health analysis in social media

AH Yazdavar, MS Mahdavinejad, G Bajaj, W Romine… - Plos one, 2020 - journals.plos.org
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 …

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 …

Artificial neural network and latent semantic analysis for adverse drug reaction detection

AA Nafea, N Omar, ZM Al-qfail - Baghdad Science Journal, 2024 - bsj.uobaghdad.edu.iq
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 …

[PDF][PDF] Adverse drug reaction detection using latent semantic analysis

AA Nafea, N Omar, MM AL-Ani - J. Comput. Sci, 2021 - academia.edu
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 …

An ensemble model for detection of adverse drug reactions

AA Nafea, MS Ibrahim, AA Mukhlif… - ARO-The Scientific …, 2024 - 88.198.206.215
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 …

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 …

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 …