AIMC Topic: Pharmacovigilance

Clear Filters Showing 71 to 80 of 105 articles

An ensemble method for extracting adverse drug events from social media.

Artificial intelligence in medicine Jun 6, 2016
OBJECTIVE: Because adverse drug events (ADEs) are a serious health problem and a leading cause of death, it is of vital importance to identify them correctly and in a timely manner. With the development of Web 2.0, social media has become a large dat...
Humans Pharmacovigilance Semantics Internet Drug-Related Side Effects and Adverse Reactions Data Mining Social Media Natural Language Processing
View on PubMed DOI

Predictive modeling of structured electronic health records for adverse drug event detection.

BMC medical informatics and decision making Nov 25, 2015
BACKGROUND: The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. Th...
Databases, Factual Computer Simulation Drug-Related Side Effects and Adverse Reactions Pharmacovigilance Electronic Health Records Algorithms Humans Forecasting Machine Learning Patient Safety
View on PubMed DOI

Pharmacovigilance through the development of text mining and natural language processing techniques.

Journal of biomedical informatics Nov 4, 2015
Data Mining Pharmacovigilance Natural Language Processing
View on PubMed DOI

Text mining for pharmacovigilance: Using machine learning for drug name recognition and drug-drug interaction extraction and classification.

Journal of biomedical informatics Sep 30, 2015
Pharmacovigilance (PV) is defined by the World Health Organization as the science and activities related to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem. An essential aspect in PV is to ...
Machine Learning Drug Interactions Data Mining Pharmacovigilance
View on PubMed DOI

On the creation of a clinical gold standard corpus in Spanish: Mining adverse drug reactions.

Journal of biomedical informatics Jun 30, 2015
The advances achieved in Natural Language Processing make it possible to automatically mine information from electronically created documents. Many Natural Language Processing methods that extract information from texts make use of annotated corpora,...
Linguistics Translating Drug-Related Side Effects and Adverse Reactions Data Mining Automation Adverse Drug Reaction Reporting Systems Predictive Value of Tests Pharmacovigilance Natural Language Processing Pharmaceutical Preparations Language Reproducibility of Results Machine Learning Algorithms Electronic Health Records
View on PubMed DOI

Exploring Spanish health social media for detecting drug effects.

BMC medical informatics and decision making Jun 15, 2015
BACKGROUND: Adverse Drug reactions (ADR) cause a high number of deaths among hospitalized patients in developed countries. Major drug agencies have devoted a great interest in the early detection of ADRs due to their high incidence and increasing hea...
Language Social Media Natural Language Processing Data Mining Internet Information Dissemination Humans Drug-Related Side Effects and Adverse Reactions Machine Learning Pharmacovigilance
View on PubMed DOI

Toward a complete dataset of drug-drug interaction information from publicly available sources.

Journal of biomedical informatics Apr 24, 2015
Although potential drug-drug interactions (PDDIs) are a significant source of preventable drug-related harm, there is currently no single complete source of PDDI information. In the current study, all publically available sources of PDDI information ...
Databases, Factual Adverse Drug Reaction Reporting Systems Machine Learning Data Mining Pharmacovigilance Internet Database Management Systems Natural Language Processing Medical Record Linkage Drug Interactions
View on PubMed DOI

Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.

Journal of the American Medical Informatics Association : JAMIA Mar 9, 2015
OBJECTIVE: Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural la...
Pharmacovigilance Semantics Social Media Natural Language Processing Data Mining Humans Artificial Intelligence
View on PubMed DOI

Detecting Adverse Drug Events in Clinical Notes Using Large Language Models.

Studies in health technology and informatics May 15, 2025
Monitoring adverse drug events (ADEs) is critical for pharmacovigilance and patient safety. However, identifying ADEs remains challenging, as suspected or confirmed side effects are often documented solely in the unstructured text of electronic healt...
Humans Electronic Health Records Pharmacovigilance Adverse Drug Reaction Reporting Systems Large Language Models Drug-Related Side Effects and Adverse Reactions Data Mining Natural Language Processing
View on PubMed DOI

Leveraging Generative AI for Drug Safety and Pharmacovigilance.

Current reviews in clinical and experimental pharmacology Jan 1, 2025
Predictions are made by artificial intelligence, especially through machine learning, which uses algorithms and past knowledge. Notably, there has been an increase in interest in using artificial intelligence, particularly generative AI, in the pharm...
Adverse Drug Reaction Reporting Systems Drug-Related Side Effects and Adverse Reactions Pharmacovigilance Artificial Intelligence Humans Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals