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Adverse drug reactions / events (ADR/ADE) have a major impact on patient health and health care costs. Detecting ADR's as early as possible and sharing them with regulators, pharma companies, and healthcare providers can prevent morbidity…

Computation and Language · Computer Science 2022-01-07 Hasham Ul Haq , Veysel Kocaman , David Talby

Much recent research aims to identify evidence for Drug-Drug Interactions (DDI) and Adverse Drug reactions (ADR) from the biomedical scientific literature. In addition to this "Bibliome", the universe of social media provides a very…

Social and Information Networks · Computer Science 2016-01-15 Rion Brattig Correia , Lang Li , Luis M. Rocha

Adverse Drug Reaction (ADR) is a significant public health concern world-wide. Numerous graph-based methods have been applied to biomedical graphs for predicting ADRs in pre-marketing phases. ADR detection in post-market surveillance is no…

Machine Learning · Computer Science 2020-04-02 Heeyoung Kwak , Minwoo Lee , Seunghyun Yoon , Jooyoung Chang , Sangmin Park , Kyomin Jung

Adverse drug reaction (ADR) prediction plays a crucial role in both health care and drug discovery for reducing patient mortality and enhancing drug safety. Recently, many studies have been devoted to effectively predict the drug-ADRs…

Information Retrieval · Computer Science 2023-08-08 Haoxuan Li , Taojun Hu , Zetong Xiong , Chunyuan Zheng , Fuli Feng , Xiangnan He , Xiao-Hua Zhou

Adverse Drug Reactions (ADRs) are a leading cause of morbidity and mortality. Existing prediction methods rely mainly on chemical similarity, machine learning on structured databases, or isolated target profiles, but often fail to integrate…

Biomolecules · Quantitative Biology 2026-03-03 David Jackson , Michael Gertz , Jürgen Hesser

Combination pharmacotherapy offers substantial therapeutic advantages but also poses substantial risks of adverse drug reactions (ADRs). The accurate prediction of ADRs with interpretable computational methods is crucial for clinical safety…

Machine Learning · Computer Science 2026-03-17 Y. Cheung

Minimizing adverse reactions caused by drug-drug interactions has always been a momentous research topic in clinical pharmacology. Detecting all possible interactions through clinical studies before a drug is released to the market is a…

Artificial Intelligence · Computer Science 2018-03-13 Meng Wang

With the increase in popularity of deep learning models for natural language processing (NLP) tasks, in the field of Pharmacovigilance, more specifically for the identification of Adverse Drug Reactions (ADRs), there is an inherent need for…

Information Retrieval · Computer Science 2020-04-01 Ramya Tekumalla , Juan M. Banda

Drug-drug interactions (DDIs) are a major concern in polypharmacy. Public databases often provide only qualitative descriptions without pharmacokinetic context. We present an interactive web tool that integrates 191,541 descriptive DDI…

Quantitative Methods · Quantitative Biology 2025-08-13 Nadezhda Diadkina

Adverse drug reactions (ADRs) are big concern for public health. ADRs are one of most common causes to withdraw some drugs from markets. Now two major methods for detecting ADRs are spontaneous reporting system (SRS), and prescription event…

Computational Engineering, Finance, and Science · Computer Science 2013-09-02 Yihui Liu , Uwe Aickelin

Adverse drug reaction (ADR) is widely concerned for public health issue. ADRs are one of most common causes to withdraw some drugs from market. Prescription event monitoring (PEM) is an important approach to detect the adverse drug…

Machine Learning · Computer Science 2014-09-03 Yihui Liu , Uwe Aickelin

Modelling disease progression of iron deficiency anaemia (IDA) following oral iron supplement prescriptions is a prerequisite for evaluating the cost-effectiveness of oral iron supplements. Electronic health records (EHRs) from the Clinical…

Applications · Statistics 2021-07-30 Li Su , Yafeng Cheng , Dora I. A. Pereira , Jonathan J. Powell

Recent years have witnessed the rapid accumulation of massive electronic medical records (EMRs), which highly support the intelligent medical services such as drug recommendation. However, prior arts mainly follow the traditional…

Information Retrieval · Computer Science 2021-02-09 Zhi Zheng , Chao Wang , Tong Xu , Dazhong Shen , Penggang Qin , Baoxing Huai , Tongzhu Liu , Enhong Chen

The automation of adverse drug reaction (ADR) detection in social media would revolutionize the practice of pharmacovigilance, supporting drug regulators, the pharmaceutical industry and the general public in ensuring the safety of the…

Computation and Language · Computer Science 2020-05-15 Amy Breden , Lee Moore

Adverse drug reactions (ADRs) are a major barrier to safe and effective pharmacotherapy and increasingly reflect higher order interactions between drugs, genetic background, and clinical phenotypes. Existing graph based approaches usually…

Quantitative Methods · Quantitative Biology 2025-12-02 Ze Cai , Haotian Tang , Shuai Gao , Binbin Zhou , Junhan Zhao , Jun Wen

Adverse drug reaction (ADR) is widely concerned for public health issue. ADRs are one of most common causes to withdraw some drugs from market. Prescription event monitoring (PEM) is an important approach to detect the adverse drug…

Computational Engineering, Finance, and Science · Computer Science 2013-07-08 Yihui Liu , Uwe Aickelin

Adverse drug reaction (ADR) detection is an essential task in the medical field, as ADRs have a gravely detrimental impact on patients' health and the healthcare system. Due to a large number of people sharing information on social media…

Computation and Language · Computer Science 2023-08-21 Yunzhi Qiu , Xiaokun Zhang , Weiwei Wang , Tongxuan Zhang , Bo Xu , Hongfei Lin

Despite extensive safety assessments of drugs prior to their introduction to the market, certain adverse drug reactions (ADRs) remain undetected. The primary objective of pharmacovigilance is to identify these ADRs (i.e., signals). In…

Methodology · Statistics 2024-04-23 Louis Dijkstra , Tania Schink , Ronja Foraita

Drug repurposing identifies new therapeutic uses for existing drugs, reducing the time and costs compared to traditional de novo drug discovery. Most existing drug repurposing studies using real-world patient data often treat the entire…

Machine Learning · Computer Science 2024-12-31 Seungyeon Lee , Ruoqi Liu , Feixiong Cheng , Ping Zhang

Automatic monitoring of adverse drug events (ADEs) or reactions (ADRs) is currently receiving significant attention from the biomedical community. In recent years, user-generated data on social media has become a valuable resource for this…

Computation and Language · Computer Science 2023-11-21 Ilseyar Alimova , Elena Tutubalina
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