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Related papers: Extracting Adverse Drug Events from Clinical Notes

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Adverse reaction caused by drugs is a potentially dangerous problem which may lead to mortality and morbidity in patients. Adverse Drug Event (ADE) extraction is a significant problem in biomedical research. We model ADE extraction as a…

Computation and Language · Computer Science 2018-01-03 Suriyadeepan Ramamoorthy , Selvakumar Murugan

An adverse drug effect (ADE) is any harmful event resulting from medical drug treatment. Despite their importance, ADEs are often under-reported in official channels. Some research has therefore turned to detecting discussions of ADEs in…

Computation and Language · Computer Science 2024-07-03 Dorothea MacPhail , David Harbecke , Lisa Raithel , Sebastian Möller

Adverse drug reactions (ADRs) are unwanted or harmful effects experienced after the administration of a certain drug or a combination of drugs, presenting a challenge for drug development and drug administration. In this paper, we present a…

Computation and Language · Computer Science 2019-05-29 Maksim Belousov , Nikola Milosevic , William Dixon , Goran Nenadic

Adverse Drug Event (ADE) extraction models can rapidly examine large collections of social media texts, detecting mentions of drug-related adverse reactions and trigger medical investigations. However, despite the recent advances in NLP, it…

Computation and Language · Computer Science 2021-09-27 Simone Scaboro , Beatrice Portelli , Emmanuele Chersoni , Enrico Santus , Giuseppe Serra

Adverse drug events (ADEs) are an important aspect of drug safety. Various texts such as biomedical literature, drug reviews, and user posts on social media and medical forums contain a wealth of information about ADEs. Recent studies have…

Computation and Language · Computer Science 2024-05-21 Shaoxiong Ji , Ya Gao , Pekka Marttinen

Adverse Event (ADE) extraction is one of the core tasks in digital pharmacovigilance, especially when applied to informal texts. This task has been addressed by the Natural Language Processing community using large pre-trained language…

Computation and Language · Computer Science 2023-06-09 Simone Scaboro , Beatrice Portellia , Emmanuele Chersoni , Enrico Santus , Giuseppe Serra

Active adverse event surveillance monitors Adverse Drug Events (ADE) from different data sources, such as electronic health records, medical literature, social media and search engine logs. Over the years, many datasets have been created,…

Computation and Language · Computer Science 2024-11-26 Xiang Dai , Sarvnaz Karimi , Abeed Sarker , Ben Hachey , Cecile Paris

Adverse drug events (ADEs) are a major safety issue in clinical trials. Thus, predicting ADEs is key to developing safer medications and enhancing patient outcomes. To support this effort, we introduce CT-ADE, a dataset for multilabel ADE…

Computation and Language · Computer Science 2025-03-11 Anthony Yazdani , Alban Bornet , Philipp Khlebnikov , Boya Zhang , Hossein Rouhizadeh , Poorya Amini , Douglas Teodoro

Timely and accurate extraction of Adverse Drug Events (ADE) from biomedical literature is paramount for public safety, but involves slow and costly manual labor. We set out to improve drug safety monitoring (pharmacovigilance, PV) through…

The mining of adverse drug events (ADEs) is pivotal in pharmacovigilance, enhancing patient safety by identifying potential risks associated with medications, facilitating early detection of adverse events, and guiding regulatory…

Artificial Intelligence · Computer Science 2024-10-04 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Aman Chadha , Samrat Mondal

We study the problem of detecting adverse drug events in electronic healthcare records. The challenge in this work is to aggregate heterogeneous data types involving diagnosis codes, drug codes, as well as lab measurements. An earlier…

Machine Learning · Computer Science 2019-07-16 Maria Bampa , Panagiotis Papapetrou

The increased adoption of Electronic Health Records(EHRs) has brought changes to the way the patient care is carried out. The rich heterogeneous and temporal data space stored in EHRs can be leveraged by machine learning models to capture…

Machine Learning · Computer Science 2019-04-11 Maria Bampa

In this study, we establish a benchmark for adverse drug event (ADE) detection in Dutch clinical free-text documents using several transformer models, clinical scenarios, and fit-for-purpose performance measures. We trained a Bidirectional…

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 reactions (ADRs) are one of the leading causes of mortality in health care. Current ADR surveillance systems are often associated with a substantial time lag before such events are officially published. On the other hand,…

Information Retrieval · Computer Science 2018-02-15 Shashank Gupta , Manish Gupta , Vasudeva Varma , Sachin Pawar , Nitin Ramrakhiyani , Girish K. Palshikar

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

Adverse drug reactions (ADRs) are one of the leading causes of mortality in health care. Current ADR surveillance systems are often associated with a substantial time lag before such events are officially published. On the other hand,…

Information Retrieval · Computer Science 2018-02-15 Shashank Gupta , Manish Gupta , Vasudeva Varma , Sachin Pawar , Nitin Ramrakhiyani , Girish K. Palshikar

Post--marketing pharmacovigilance is essential for identifying adverse drug reactions (ADRs) that elude detection during pre--marketing clinical trials. This study explores a novel approach that integrates an adverse event (AE) ontology…

Adverse drug events (ADEs) are a serious health problem that can be life-threatening. While a lot of studies have been performed on detect correlation between a drug and an AE, limited studies have been conducted on personalized ADE risk…

Machine Learning · Computer Science 2021-04-20 Jinhe Shi , Xiangyu Gao , Chenyu Ha , Yage Wang , Guodong Gao , Yi Chen

Extraction of adverse drug events from biomedical literature and other textual data is an important component to monitor drug-safety and this has attracted attention of many researchers in healthcare. Existing works are more pivoted around…

Computation and Language · Computer Science 2021-10-22 Harshit Jain , Nishant Raj , Suyash Mishra
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