Research graph
References from Integration of artificial intelligence into pharmacovigilance: A systematic review. Local targets link to admitted publications; unresolved targets remain external evidence.
Unresolved reference
2002 · External reference
Innovation in pharmacovigilance: use of artificial intelligence in adverse event case processing
10.1002/cpt.1255 · 2019 · External reference
Artificial intelligence, real-world automation and the safety of medicines
10.1007/s40264-020-01001-7 · 2021 · External reference
The use of artificial intelligence in pharmacovigilance: a systematic review of the literature
10.1007/s40290-022-00441-z · 2022 · External reference
Unresolved reference
1979 · External reference
Process analytical technology in the pharmaceutical industry: a toolkit for continuous improvement
2006 · External reference
Artificial intelligence, machine learning and deep learning: definitions and differences
10.1111/ced.14029 · 2020 · External reference
Unresolved reference
2025 · External reference
Artificial intelligence for drug toxicity and safety
10.1016/j.tips.2019.07.005 · 2019 · External reference
Artificial intelligence based on machine learning in pharmacovigilance: a scoping review
10.1007/s40264-022-01176-1 · 2022 · External reference
Using machine learning for pharmacovigilance: a systematic review
10.3390/pharmaceutics14020266 · 2022 · External reference
Machine learning applications in pharmacovigilance: scoping review
2023 · External reference
Safeguarding patients in the AI era: ethics at the forefront of pharmacovigilance
2024 · External reference
Artificial intelligence (AI) in pharmacovigilance: a systematic review on predicting adverse drug reactions (ADR) in hospitalized patients
10.1016/j.sapharm.2025.02.008 · 2025 · External reference
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
2021 · External reference
Updated methodological guidance for the conduct of scoping reviews
10.1097/xeb.0000000000000277 · 2021 · External reference
Unresolved reference
2013 · External reference
APPRAISE-AI tool for quantitative evaluation of AI studies for clinical decision support
10.1001/jamanetworkopen.2023.35377 · 2023 · External reference
Chapter 21: qualitative evidence
2023 · External reference
Unresolved reference
2013 · External reference
IL-4/13 blockade and sleep-related adverse drug reactions in over 37,000 Dupilumab reports from the world health organization individual case safety reporting pharmacovigilance database (VigiBase™): a big data and machine learning analysis
2022 · External reference
From similarities to probabilities: feature engineering for predicting drugs' adverse reactions
10.32604/iasc.2022.022104 · 2022 · External reference
ADE eval: an evaluation of text processing systems for adverse event extraction from drug labels for pharmacovigilance
10.1007/s40264-020-00996-3 · 2021 · External reference
Investigating ADR mechanisms with explainable AI: a feasibility study with knowledge graph mining
10.1186/s12911-021-01518-6 · 2021 · External reference
Using GPT-3 to build a lexicon of drugs of abuse synonyms for social media pharmacovigilance
10.3390/biom13020387 · 2023 · External reference
Automatic text classification of drug-induced liver injury using document-term matrix and XGBoost
10.3389/frai.2024.1401810 · 2024 · External reference
Data-driven identification of factors that influence the quality of adverse event reports: 15-year interpretable machine learning and time-series analyses of VigiBase and QUEST
10.2196/49643 · 2024 · External reference
Text mining of adverse events in clinical trials: deep learning approach
10.2196/28632 · 2021 · External reference
Advancing medical imaging: detecting polypharmacy and adverse drug effects with graph convolutional networks (GCN)
10.1186/s12880-024-01349-7 · 2024 · External reference
Adverse drug event prediction using noisy literature-derived knowledge graphs: algorithm development and validation
10.2196/32730 · 2021 · External reference
Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort
10.1371/journal.pcbi.1009053 · 2021 · External reference
Evaluation of four machine learning models for signal detection
10.1177/20420986231219472 · 2023 · External reference
A pilot, predictive surveillance model in pharmacovigilance using machine learning approaches
10.1007/s12325-024-02870-5 · 2024 · External reference
Cold-start problems in data-driven prediction of drug–drug interaction effects
10.3390/ph14050429 · 2021 · External reference
Provision and characterization of a corpus for pharmaceutical, biomedical named entity recognition for pharmacovigilance: evaluation of language registers and training data sufficiency
10.1007/s40264-023-01322-3 · 2023 · External reference
Broadening the capture of natural products mentioned in FAERS using fuzzy string-matching and a Siamese neural network
10.1038/s41598-023-51004-4 · 2024 · External reference
Automated gathering of real-world data from online patient forums can complement pharmacovigilance for rare cancers
10.1038/s41598-022-13894-8 · 2022 · External reference
BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices
10.3389/fpubh.2024.1392180 · 2024 · External reference
Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning
10.1093/jamia/ocab014 · 2021 · External reference
Deep learning approaches for extracting adverse events and indications of dietary supplements from clinical text
10.1093/jamia/ocaa218 · 2021 · External reference
Development of a multivariate prediction model to identify individual case safety reports which require clinical review
10.1002/pds.5553 · 2022 · External reference
Predicting adverse drug reactions from social media posts: data balance, feature selection and deep learning
2022 · External reference
Pharmacovigilance with transformers: a framework to detect adverse drug reactions using BERT fine-tuned with FARM
10.1155/2021/5589829 · 2021 · External reference
Artificial intelligence-enabled social media analysis for pharmacovigilance of COVID-19 vaccinations in the United Kingdom: observational study
10.2196/32543 · 2022 · External reference
Similarity-based machine learning framework for predicting safety signals of adverse drug–drug interactions
10.1016/j.imu.2021.100699 · 2021 · External reference
Supervised machine learning-based decision support for signal validation classification
10.1007/s40264-022-01159-2 · 2022 · External reference
Improved adverse drug event prediction through information component guided pharmacological network model (IC-PNM)
10.1109/tcbb.2019.2928305 · 2021 · External reference
Extraction of medication-effect relations in Twitter data with neural embedding and recurrent neural network
2022 · External reference
A real-world pharmacovigilance study on cardiovascular adverse events of tisagenlecleucel using machine learning approach
10.1038/s41598-024-64466-x · 2024 · External reference
Integrating machine learning with electronic health record data to facilitate detection of prolactin level and pharmacovigilance signals in olanzapine-treated patients
10.3389/fendo.2022.1011492 · 2022 · External reference
Automatic extraction of comprehensive drug safety information from adverse drug event narratives in the Korea adverse event reporting system using natural language processing techniques
10.1007/s40264-023-01323-2 · 2023 · External reference
Machine learning approach for active vaccine safety monitoring
10.3346/jkms.2021.36.e198 · 2021 · External reference
Using natural language processing to characterize and predict homeopathic product-associated adverse events in consumer reviews: comparison to reports to FDA adverse event reporting System (FAERS)
10.1093/jamia/ocad197 · 2023 · External reference
MultiGML: multimodal graph machine learning for prediction of adverse drug events
10.1016/j.heliyon.2023.e19441 · 2023 · External reference
Detecting early safety signals of infliximab using machine learning algorithms in the Korea adverse event reporting system
2022 · External reference
Artificial intelligence for unstructured healthcare data: application to coding of patient reporting of adverse drug reactions
10.1002/cpt.2266 · 2021 · External reference
Using a machine learning approach to monitor COVID-19 Vaccine adverse events (VAE) from Twitter data
2022 · External reference
DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter
10.1093/jamia/ocab114 · 2021 · External reference
Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance
10.1016/j.jbi.2021.103719 · 2021 · External reference
LiSA: an assisted literature search pipeline for detecting serious adverse drug events with deep learning
10.1186/s12911-022-02085-0 · 2022 · External reference
Validation of artificial intelligence to support the automatic coding of patient adverse drug reaction reports, using nationwide pharmacovigilance data
10.1007/s40264-022-01153-8 · 2022 · External reference
Deep learning prediction of adverse drug reactions in drug discovery using open TG–GATEs and FAERS databases
10.3389/fddsv.2021.768792 · 2021 · External reference
Named entity recognition in pubmed abstracts for pharmacovigilance using deep learning
2022 · External reference
Toward AI-supported evaluation for safety control measures against near-miss events in pharmaceutical products
10.1016/j.ssci.2023.106314 · 2023 · External reference
Identifying adverse drug reactions from patient reviews on social media using natural language processing
10.1177/14604582221136712 · 2023 · External reference
Artificial intelligent context-aware machine-learning tool to detect adverse drug events from social media platforms
10.1007/s13181-022-00906-2 · 2022 · External reference
Target adverse event profiles for predictive safety in the postmarket setting
10.1002/cpt.2074 · 2021 · External reference
Big data- and machine learning-based analysis of a global pharmacovigilance database enables the discovery of sex-specific differences in the safety profile of dual IL4/IL13 blockade
10.3389/fphar.2023.1271309 · 2023 · External reference
SubGE-DDI: a new prediction model for drug-drug interaction established through biomedical texts and drug-pairs knowledge subgraph enhancement
10.1371/journal.pcbi.1011989 · 2024 · External reference
Prediction of drug-induced long QT syndrome using machine learning applied to harmonized electronic health record data
10.1177/1074248421995348 · 2021 · External reference
Artificial intelligence-enabled software prototype to inform opioid pharmacovigilance from electronic health records: development and usability study
10.2196/45000 · 2023 · External reference
Sentence-level aspect-based sentiment analysis for classifying adverse drug reactions (ADRs) using hybrid Ontology-XLNet transfer learning
10.1109/access.2021.3091394 · 2021 · External reference
The Russian drug reaction corpus and neural models for drug reactions and effectiveness detection in user reviews
10.1093/bioinformatics/btaa675 · 2021 · External reference
Adverse drug reaction discovery using a tumor-biomarker knowledge graph
10.3389/fgene.2020.625659 · 2021 · External reference
InferBERT: a transformer-based causal inference framework for enhancing pharmacovigilance
10.3389/frai.2021.659622 · 2021 · External reference
Deep learning models in detection of dietary supplement adverse event signals from Twitter
10.1093/jamiaopen/ooab081 · 2021 · External reference
Streamlining considerations for safety measures: a predictive model for addition of clinically significant adverse reactions to Japanese drug package inserts
10.1248/bpb.b23-00846 · 2024 · External reference
Predicting the addition of information regarding clinically significant adverse drug reactions to Japanese drug package inserts using a machine-learning model
10.1007/s43441-023-00603-4 · 2024 · External reference
Evaluating drug risk using GAN and SMOTE based on CFDA's spontaneous reporting data
10.1155/2021/6033860 · 2021 · External reference
Chinese-named entity recognition from adverse drug event records: radical embedding-combined dynamic embedding-based BERT in a bidirectional long short-term conditional random field (Bi-LSTM-CRF) model
10.2196/26407 · 2021 · External reference
Data mining methodology for response to hypertension symptomology-application to COVID-19-related pharmacovigilance
2021 · External reference
An assessment of mentions of adverse drug events on social media with natural language processing: model development and analysis
10.2196/38140 · 2022 · External reference
Predicting adverse drug events in Chinese pediatric inpatients with the associated risk factors: a machine learning study
2021 · External reference
Identifying the serious clinical outcomes of adverse reactions to drugs by a multi-task deep learning framework
10.1038/s42003-023-05243-w · 2023 · External reference
Identifying cases of shoulder injury related to vaccine administration (SIRVA) in the United States: development and validation of a natural language processing method
10.2196/30426 · 2022 · External reference
Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records
10.1111/bcpt.13773 · 2022 · External reference
Quantifying the severity of adverse drug reactions using social media: network analysis
10.2196/27714 · 2021 · External reference
A scalable tree boosting system
2016 · External reference
BERT: Pre-training of deep bidirectional transformers for language understanding
2019 · External reference
Big data and adverse drug reaction detection
10.1002/cpt.302 · 2016 · External reference
Comprehensive review of drug–drug interaction prediction based on machine learning: current status, challenges, and opportunities
10.1021/acs.jcim.3c01304 · 2024 · External reference
How can artificial intelligence decrease cognitive and work burden for front line practitioners?
10.1093/jamiaopen/ooad079 · 2023 · External reference
Clinicians' perceptions of artificial intelligence: focus on workload, risk, trust, clinical decision making
2023 · External reference
Effect of uncertainty-aware AI models on pharmacists' reaction time and decision-making in a web-based mock medication verification task: randomized controlled trial
2025 · External reference
Utilizing advanced technologies to augment pharmacovigilance systems: challenges and opportunities
10.1007/s43441-019-00023-3 · 2020 · External reference
Industry perspective on artificial intelligence/machine learning in pharmacovigilance: perspective on AI and ML in PV
10.1007/s40264-022-01164-5 · 2022 · External reference
Automation Opportunities in Pharmacovigilance: an Industry Survey: R. Ghosh et al
10.1007/s40290-019-00320-0 · 2020 · External reference
Unresolved reference
2024 · External reference
Unresolved reference
2025 · External reference
Ethical and legal challenges of artificial intelligence-driven healthcare
2020 · External reference
Advancing an agile regulatory ecosystem to respond to the rapid development of innovative technologies
10.1111/cts.13267 · 2022 · External reference
Using artificial intelligence & machine learning in the development of drug & biological product
2025 · External reference
General data protection regulation
2018 · External reference
Secure, privacy-preserving and federated machine learning in medical imaging
10.1038/s42256-020-0186-1 · 2020 · External reference
International conference on harmonisation; E2B (R3) electronic transmission of individual case safety reports; data elements and message specification; appendix on backwards and forwards compatibility; availability. Notice
2014 · External reference
Validating Intelligent Automation Systems in Pharmacovigilance: insights from Good Manufacturing Practices: K. Huysentruyt et al
10.1007/s40264-020-01030-2 · 2021 · External reference
Artificial intelligence in pharmacovigilance–opportunities and challenges
10.4103/picr.picr_290_23 · 2024 · External reference
Algorithmic fairness in artificial intelligence for medicine and healthcare
10.1038/s41551-023-01056-8 · 2023 · External reference
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning
10.1038/s42256-023-00697-3 · 2023 · External reference
Medication without harm: who's third global patient safety challenge
10.1016/s0140-6736(17)31047-4 · 2017 · External reference
Dissecting racial bias in an algorithm used to manage the health of populations
10.1126/science.aax2342 · 2019 · External reference
Unresolved reference
2023 · External reference
