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Text classification models for the automatic detection of nonmedical prescription medication use from social media

BMC medical informatics and decision making, 2021-01, Vol.21 (1), p.27-27, Article 27

2021

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Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set

Journal of medical Internet research, 2021-01, Vol.23 (1), p.e25314-e25314

2021

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Promoting Reproducible Research for Characterizing Nonmedical Use of Medications Through Data Annotation: Description of a Twitter Corpus and Guidelines

Journal of medical Internet research, 2020-02, Vol.22 (2), p.e15861-e15861

2020

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Social Media Posts on Statins: What Can We Learn About Patient Experiences and Perspectives?

Journal of the American Heart Association, 2024-04, Vol.13 (7), p.e033992-e033992

2024

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The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review

JMIR research protocols, 2023-08, Vol.12, p.e47068-e47068

2023

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Public Perspectives on Anti-Diabetic Drugs: Exploratory Analysis of Twitter Posts

JMIR diabetes, 2021-01, Vol.6 (1), p.e24681-e24681

2021

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Science: The Potential and the Challenges of Utilizing Social Media and Other Electronic Communication Platforms in Health Care

Clinical and translational science, 2020-01, Vol.13 (1), p.26-30

2020

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ChatGPT and large language models in academia: opportunities and challenges

BioData mining, 2023-07, Vol.16 (1), p.20-11, Article 20

2023

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Deep neural networks ensemble for detecting medication mentions in tweets

Journal of the American Medical Informatics Association : JAMIA, 2019-12, Vol.26 (12), p.1618-1626

2019

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Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review

Journal of medical Internet research, 2022-04, Vol.24 (4), p.e35788-e35788

2022

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Pregnancy and health in the age of the Internet: A content analysis of online "birth club" forums

PloS one, 2020-04, Vol.15 (4), p.e0230947

2020

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ReportAGE: Automatically extracting the exact age of Twitter users based on self-reports in tweets

PloS one, 2022-01, Vol.17 (1), p.e0262087-e0262087

2022

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DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter

Journal of the American Medical Informatics Association : JAMIA, 2021-10, Vol.28 (10), p.2184-2192

2021

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Automatically Identifying Self-Reports of COVID-19 Diagnosis on Twitter: An Annotated Data Set, Deep Neural Network Classifiers, and a Large-Scale Cohort

Journal of medical Internet research, 2023-07, Vol.25 (1), p.e46484-e46484

2023

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Pregex: Rule-Based Detection and Extraction of Twitter Data in Pregnancy

Journal of medical Internet research, 2023-02, Vol.25 (1), p.e40569-e40569

2023

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Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter

JAMA network open, 2019-11, Vol.2 (11), p.e1914672-e1914672

2019

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Social media mining for birth defects research: A rule-based, bootstrapping approach to collecting data for rare health-related events on Twitter

Journal of biomedical informatics, 2018-11, Vol.87, p.68-78

2018

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Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers

Journal of medical Internet research, 2024-03, Vol.26 (4), p.e50652-e50652

2024

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Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping Review

Journal of medical Internet research, 2024-03, Vol.26, p.e47923-e47923

2024

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Active neural networks to detect mentions of changes to medication treatment in social media

Journal of the American Medical Informatics Association : JAMIA, 2021-11, Vol.28 (12), p.2551-2561

2021

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Reasons for Discontinuation or Change of Selective Serotonin Reuptake Inhibitors in Online Drug Reviews

JAMA network open, 2023-07, Vol.6 (7), p.e2323746-e2323746

2023

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The Value of Social Media Analysis for Adverse Events Detection and Pharmacovigilance: Scoping Review

JMIR public health and surveillance, 2024-09, Vol.10, p.e59167

2024

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An annotated data set for identifying women reporting adverse pregnancy outcomes on Twitter

Data in brief, 2020-10, Vol.32, p.106249-106249, Article 106249

2020

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Using Twitter Data for Cohort Studies of Drug Safety in Pregnancy: Proof-of-concept With β-Blockers

JMIR formative research, 2022-06, Vol.6 (6), p.e36771-e36771

2022

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Toward Using Twitter Data to Monitor COVID-19 Vaccine Safety in Pregnancy: Proof-of-Concept Study of Cohort Identification

JMIR formative research, 2022-01, Vol.6 (1), p.e33792-e33792

2022

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Text classification models for the automatic detection of nonmedical prescription medication use from social media

Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set

Promoting Reproducible Research for Characterizing Nonmedical Use of Medications Through Data Annotation: Description of a Twitter Corpus and Guidelines

Social Media Posts on Statins: What Can We Learn About Patient Experiences and Perspectives?

The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review

Public Perspectives on Anti-Diabetic Drugs: Exploratory Analysis of Twitter Posts

Science: The Potential and the Challenges of Utilizing Social Media and Other Electronic Communication Platforms in Health Care

ChatGPT and large language models in academia: opportunities and challenges

Deep neural networks ensemble for detecting medication mentions in tweets

Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review

Pregnancy and health in the age of the Internet: A content analysis of online "birth club" forums

ReportAGE: Automatically extracting the exact age of Twitter users based on self-reports in tweets

DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter

Automatically Identifying Self-Reports of COVID-19 Diagnosis on Twitter: An Annotated Data Set, Deep Neural Network Classifiers, and a Large-Scale Cohort

Pregex: Rule-Based Detection and Extraction of Twitter Data in Pregnancy

Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter

Social media mining for birth defects research: A rule-based, bootstrapping approach to collecting data for rare health-related events on Twitter

Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers

Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping Review

Active neural networks to detect mentions of changes to medication treatment in social media

Reasons for Discontinuation or Change of Selective Serotonin Reuptake Inhibitors in Online Drug Reviews

The Value of Social Media Analysis for Adverse Events Detection and Pharmacovigilance: Scoping Review

An annotated data set for identifying women reporting adverse pregnancy outcomes on Twitter

Using Twitter Data for Cohort Studies of Drug Safety in Pregnancy: Proof-of-concept With β-Blockers

Toward Using Twitter Data to Monitor COVID-19 Vaccine Safety in Pregnancy: Proof-of-Concept Study of Cohort Identification

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