Adverse Drug

Adverse drug reactions (ADRs) pose a significant threat to patient safety, driving research into accurate and efficient detection methods. Current research focuses on developing sophisticated machine learning models, including deep learning architectures like convolutional neural networks and transformers, often augmented with knowledge graphs and multimodal data (text and images) to improve ADR prediction and classification from diverse sources such as clinical trials, social media, and patient forums. These advancements aim to enhance pharmacovigilance, enabling earlier identification of potential risks and improved medication safety guidelines.

Papers

October 24, 2024

Lived Experience Not Found: LLMs Struggle to Align with Experts on Addressing Adverse Drug Reactions from Psychiatric Medication Use
Mohit Chandra, Siddharth Sriraman, Gaurav Verma, Harneet Singh Khanuja, Jose Suarez Campayo, Zihang Li, Michael L. Birnbaum, Munmun De Choudhury
Large Language Model Expert Knowledge Mental Health Adverse Drug Adverse Drug Reaction

July 23, 2024

Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learning
Yufeng Li, Wenchao Zhao, Bo Dang, Xu Yan, Weimin Wang, Min Gao, Mingxuan Xiao
Deep Learning Knowledge Graph DH Research Drug Feature Adverse Drug Adverse Drug Reaction

July 2, 2024

Evaluating the Robustness of Adverse Drug Event Classification Models Using Templates
Dorothea MacPhail, David Harbecke, Lisa Raithel, Sebastian Möller
Native Robustness Comprehensive Evaluation Deep Template Side Effect Adverse Drug Placebo Effect

June 15, 2024

Automating Pharmacovigilance Evidence Generation: Using Large Language Models to Produce Context-Aware SQL
Jeffery L. Painter, Venkateswara Rao Chalamalasetti, Raymond Kassekert, Andrew Bate
Adverse Drug Pharmacovigilance Event Extraction Adverse Event Drug Safety

May 24, 2024

Enhancing Adverse Drug Event Detection with Multimodal Dataset: Corpus Creation and Model Development
Pranab Sahoo, Ayush Kumar Singh, Sriparna Saha, Aman Chadha, Samrat Mondal
Multimodal Dataset Model Development Corpus Creation Adverse Drug Pharmacovigilance Event Extraction Adverse Drug Event

April 19, 2024

CT-ADE: An Evaluation Benchmark for Adverse Drug Event Prediction from Clinical Trial Results
Anthony Yazdani, Alban Bornet, Philipp Khlebnikov, Boya Zhang, Hossein Rouhizadeh, Poorya Amini, Douglas Teodoro
Evaluation Benchmark Clinical Trial Drug Feature Adverse Drug CT Dataset Adverse Drug Event ADMET Prediction

March 27, 2024

A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
Lisa Raithel, Hui-Syuan Yeh, Shuntaro Yada, Cyril Grouin, Thomas Lavergne, Aurélie Névéol, Patrick Paroubek, Philippe Thomas, Tomohiro Nishiyama, Sebastian Möller, Eiji Aramaki, Yuji Matsumoto, Roland Roller, Pierre Zweigenbaum
Data Set Large Corpus Multilingual Language Model Unknown Language Multilingual Corpus Adverse Drug Clinical Corpus Pharmacovigilance Event Extraction Adverse Event

August 18, 2023

KESDT: knowledge enhanced shallow and deep Transformer for detecting adverse drug reactions
Yunzhi Qiu, Xiaokun Zhang, Weiwei Wang, Tongxuan Zhang, Bo Xu, Hongfei Lin
Knowledge Based Deep Transformer Shallow Water Adverse Drug Adverse Event Adverse Drug Reaction

August 15, 2023

DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion
Anthony Yazdani, Hossein Rouhizadeh, David Vicente Alvarez, Douglas Teodoro
Zero Shot Entity Recognition Normalization Dictionary Fine Tuned BERT Sentence Transformer Adverse Drug Rank Transformation

August 3, 2023

ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction
Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou
Multi Label Collaborative Filtering Adverse Drug Drug Representation Non Image Data

July 31, 2023

Boosting Adverse Drug Event Normalization on Social Media: General-Purpose Model Initialization and Biomedical Semantic Text Similarity Benefit Zero-Shot Linking in Informal Contexts
François Remy, Simone Scaboro, Beatrice Portelli
Zero Shot Social Medium Semantic Textual Similarity Biomedical Entity Linking Entity Normalization Adverse Drug Informal Language Model Initialization

January 25, 2023

Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection
Shaoxiong Ji, Ya Gao, Pekka Marttinen
Natural Language Processing Heterogeneous Graph Attention Network Adverse Drug Adverse Drug Event

October 21, 2022

Multimodal Model with Text and Drug Embeddings for Adverse Drug Reaction Classification
Andrey Sakhovskiy, Elena Tutubalina
Text Modality Multimodal Model Molecular Property Prediction BERT Based Molecular Descriptor Adverse Drug Drug Representation Drug Embeddings

August 3, 2022

Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient's Perspective
Lisa Raithel, Philippe Thomas, Roland Roller, Oliver Sapina, Sebastian Möller, Pierre Zweigenbaum
Data Detection Cross Lingual Clinical Text Patient Friendly Language Clinical Narrative Adverse Drug Adverse Drug Reaction

January 5, 2022

Mining Adverse Drug Reactions from Unstructured Mediums at Scale
Hasham Ul Haq, Veysel Kocaman, David Talby
Natural Language Processing Visual Analogue Scale MAESTRO Dataset Named Entity Recognition Relationship Extraction Unstructured Grid Adverse Drug

November 24, 2021

Selection of pseudo-annotated data for adverse drug reaction classification across drug groups
Ilseyar Alimova, Elena Tutubalina
Text Classification Supervised Learning Annotated Dataset View Selection Pseudo Labeled Data Adverse Drug

Adverse Drug

Papers

Lived Experience Not Found: LLMs Struggle to Align with Experts on Addressing Adverse Drug Reactions from Psychiatric Medication Use

Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learning

Evaluating the Robustness of Adverse Drug Event Classification Models Using Templates

Automating Pharmacovigilance Evidence Generation: Using Large Language Models to Produce Context-Aware SQL

Enhancing Adverse Drug Event Detection with Multimodal Dataset: Corpus Creation and Model Development

CT-ADE: An Evaluation Benchmark for Adverse Drug Event Prediction from Clinical Trial Results

A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages

KESDT: knowledge enhanced shallow and deep Transformer for detecting adverse drug reactions

DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion

ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction

Boosting Adverse Drug Event Normalization on Social Media: General-Purpose Model Initialization and Biomedical Semantic Text Similarity Benefit Zero-Shot Linking in Informal Contexts

Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection

Multimodal Model with Text and Drug Embeddings for Adverse Drug Reaction Classification

Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient's Perspective

Mining Adverse Drug Reactions from Unstructured Mediums at Scale

Selection of pseudo-annotated data for adverse drug reaction classification across drug groups