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Related papers: Drug Recommendation toward Safe Polypharmacy

200 papers

Preventable adverse drug reactions as a result of medical errors present a growing concern in modern medicine. As drug-drug interactions (DDIs) may cause adverse reactions, being able to extracting DDIs from drug labels into…

Computation and Language · Computer Science 2019-05-21 Tung Tran , Ramakanth Kavuluru , Halil Kilicoglu

Many patients with chronic diseases resort to multiple medications to relieve various symptoms, which raises concerns about the safety of multiple medication use, as severe drug-drug antagonism can lead to serious adverse effects or even…

Machine Learning · Computer Science 2023-03-07 Tian Bian , Yuli Jiang , Jia Li , Tingyang Xu , Yu Rong , Yi Su , Timothy Kwok , Helen Meng , Hong Cheng

Background: Drug-drug interactions (DDIs) refer to processes triggered by the administration of two or more drugs leading to side effects beyond those observed when drugs are administered by themselves. Due to the massive number of possible…

Quantitative Methods · Quantitative Biology 2020-12-25 Kyriakos Schwarz , Ahmed Allam , Nicolas Andres Perez Gonzalez , Michael Krauthammer

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

When patients need to take medicine, particularly taking more than one kind of drug simultaneously, they should be alarmed that there possibly exists drug-drug interaction. Interaction between drugs may have a negative impact on patients or…

Computation and Language · Computer Science 2020-08-31 Siliang Tang , Qi Zhang , Tianpeng Zheng , Mengdi Zhou , Zhan Chen , Lixing Shen , Xiang Ren , Yueting Zhuang , Shiliang Pu , Fei Wu

Drug-drug interaction (DDI) is a vital information when physicians and pharmacists intend to co-administer two or more drugs. Thus, several DDI databases are constructed to avoid mistakenly combined use. In recent years, automatically…

Computation and Language · Computer Science 2017-05-19 Zibo Yi , Shasha Li , Jie Yu , Qingbo Wu

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

Drug-drug interactions (DDIs) are a major concern in clinical practice, as they can lead to reduced therapeutic efficacy or severe adverse effects. Traditional computational approaches often struggle to capture the complex relationships…

Machine Learning · Computer Science 2025-08-27 Hongbo Liu , Siyi Li , Zheng Yu

The polypharmacy side effect prediction problem considers cases in which two drugs taken individually do not result in a particular side effect; however, when the two drugs are taken in combination, the side effect manifests. In this work,…

Databases · Computer Science 2018-10-23 Brandon Malone , Alberto García-Durán , Mathias Niepert

Managing patients with multimorbidity often results in polypharmacy: the prescription of multiple drugs. However, the long-term effects of specific combinations of drugs and diseases are typically unknown. In particular, drugs prescribed…

Artificial Intelligence · Computer Science 2016-12-12 Jessa Bekker , Arjen Hommersom , Martijn Lappenschaar , Jesse Davis

Complementary and alternative medicine are commonly used concomitantly with conventional medications leading to adverse drug reactions and even fatality in some cases. Furthermore, the vast possibility of herb-drug interactions prevents…

Artificial Intelligence · Computer Science 2023-06-28 Andreia Martins , Eva Maia , Isabel Praça

Adverse drug reaction (ADR) is widely concerned for public health issue. In this study we propose an original approach to detect the ADRs using feature matrix and feature selection. The experiments are carried out on the drug Simvastatin.…

Computational Engineering, Finance, and Science · Computer Science 2013-07-05 Yihui Liu , Uwe Aickelin

Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially in drug-drug interactions (DDIs). DDIs refer to a change in…

Revealing Adverse Drug Reactions (ADR) is an essential part of post-marketing drug surveillance, and data from health-related forums and medical communities can be of a great significance for estimating such effects. In this paper, we…

Information Retrieval · Computer Science 2017-06-20 Liliya Akhtyamova , Andrey Ignatov , John Cardiff

Co-administration of two or more drugs simultaneously can result in adverse drug reactions. Identifying drug-drug interactions (DDIs) is necessary, especially for drug development and for repurposing old drugs. DDI prediction can be viewed…

Quantitative Methods · Quantitative Biology 2022-10-21 Stuti Jain , Emilie Chouzenoux , Kriti Kumar , Angshul Majumdar

The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases and co-existing conditions. However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient.…

Machine Learning · Computer Science 2018-08-15 Marinka Zitnik , Monica Agrawal , Jure Leskovec

In Oncology, trials evaluating drug combinations are becoming more common. While combination therapies bring the potential for greater efficacy, they also create unique challenges for ensuring drug safety. In Phase-I dose escalation trials…

Applications · Statistics 2023-02-23 Lukas A. Widmer , Andrew Bean , David Ohlssen , Sebastian Weber

Drug combinations can cause adverse drug-drug interactions(DDIs). Identifying specific effects is crucial for developing safer therapies. Previous works on DDI event prediction have typically been limited to using labels of specific events…

Biomolecules · Quantitative Biology 2024-11-05 Yingying Wang , Yun Xiong , Xixi Wu , Xiangguo Sun , Jiawei Zhang

Drug-Drug Interactions (DDIs) may hamper the functionalities of drugs, and in the worst scenario, they may lead to adverse drug reactions (ADRs). Predicting all DDIs is a challenging and critical problem. Most existing computational models…

Quantitative Methods · Quantitative Biology 2023-04-19 Khaled Mohammed Saifuddin , Briana Bumgardner , Farhan Tanvir , Esra Akbas

Polypharmacy, most often defined as the simultaneous consumption of five or more drugs at once, is a prevalent phenomenon in the older population. Some of these polypharmacies, deemed inappropriate, may be associated with adverse health…

Machine Learning · Computer Science 2023-04-06 Alexandre Larouche , Audrey Durand , Richard Khoury , Caroline Sirois