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Abeed Sarker

Has grant

Associate Professor

Emory University

United States

Research Interests

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Recent Grants

Grant: Open

Mining Social Media Big Data for Toxicovigilance: Studying Substance Use via Natural Language Processing and Machine Learning Methods

Open Date: 2022-09-01

Close Date: 2027-09-01

Grant: Close

The Office of Strategy and Innovation within NCIPC OD requests expert statistical staffing

Open Date: 2020-08-01

Close Date: 2023-08-01

Grant: Close

Training in Advanced Data Analytics to End Drug-Related Harms (TADA)

Open Date: 2020-07-01

Close Date: 2025-06-30

Grant: Close

Mining Social Media Big Data for Toxicovigilance: Automating the Monitoring of Prescription Medication Abuse via Natural Language Processing and Machine Learning Methods

Open Date: 2018-07-01

Close Date: 2022-05-31

Grant: Close

Integrating Loneliness and Social Isolation Insights into Late-Life Suicide Risk Prediction Through the Digital Phenotyping of Electronic Health Records

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Collaborators (16)

Georgene Hergenroeder

Associate Professor

University of Texas Medical School at Houston

UNITED STATES

Abeed Sarker

Research Interests

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Recent Grants

Articles (22)

Governing real-world health data as a public utility

Can NLP Detect Loneliness in Electronic Health Records? A Proof-of-Concept Study

Comparing Risk Profiles of Nicotine Pouch and Smokeless Tobacco Use in U.S. Adolescents: A Machine Learning Analysis

Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Systematic Review

A cannabis use Reddit dataset for aspect-based sentiment analysis

CARE-SD: classifier-based analysis for recognizing provider stigmatizing and doubt marker labels in electronic health records: model development and validation

Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study

Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Protocol for a Systematic Review

Characterization of Reddit Posts About Xylazine-Associated Wounds: Qualitative Study

Automating inductive thematic analyses of health content using large language models: a proof-of-concept study using social media data

Building community through data: the value of a researcher driven open science ecosystem

Machine Learning and Natural Language Processing to Improve Classification of Atrial Septal Defects in Electronic Health Records.

A framework for multi-faceted content analysis of social media chatter regarding non-medical use of prescription medications

Few-shot learning for medical text: A review of advances, trends, and opportunities

Supervised Text Classification System Detects Fontan Patients in Electronic Records With Higher Accuracy Than ICD Codes

An analysis of cannabinoid hyperemesis syndrome Reddit posts and themes

The Early Detection of Fraudulent COVID-19 Products From Twitter Chatter: Data Set and Baseline Approach Using Anomaly Detection

Can accurate demographic information about people who use prescription medications nonmedically be derived from Twitter?

#ChronicPain: Automated Building of a Chronic Pain Cohort from Twitter Using Machine Learning

Evidence of the emergence of illicit benzodiazepines from online drug forums

The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges

Comparison of Pretraining Models and Strategies for Health-Related Social Media Text Classification

Collaborators (16)

Georgene Hergenroeder

Christopher Chute

Alexandra Collins

Raja Mazumder

Hannah Rogers

Lee Sanders

Jane Lowers

Dae Hee Han

Danielle Mowery

JaMor Hairston

Josh Peterson

Mohammed Al-Garadi

Martin A. Lindquist

Selen Bozkurt

Richard Moffitt

Drew Walker

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