AIMC Topic: Drug-Related Side Effects and Adverse Reactions

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Raster plots machine learning to predict the seizure liability of drugs and to identify drugs.

Scientific reports Feb 10, 2022
In vitro microelectrode array (MEA) assessment using human induced pluripotent stem cell (iPSC)-derived neurons holds promise as a method of seizure and toxicity evaluation. However, there are still issues surrounding the analysis methods used to pre...
Machine Learning Dose-Response Relationship, Drug Forecasting Seizures Pharmaceutical Preparations Female Male Adult Middle Aged Humans Cells, Cultured Toxicity Tests Liability, Legal Neural Networks, Computer Microelectrodes Drug-Related Side Effects and Adverse Reactions Induced Pluripotent Stem Cells
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Assessment of a hybrid decision support system using machine learning with artificial intelligence to safely rule out prescriptions from medication review in daily practice.

International journal of clinical pharmacy Jan 3, 2022
Background Medication review is time-consuming and not exhaustive in most French hospitals. We routinely use an innovative hybrid decision support system using Artificial Intelligence to prioritize medication review by scoring prescriptions by their ...
Artificial Intelligence Machine Learning Drug-Related Side Effects and Adverse Reactions Humans Medication Review Pharmacists Prescriptions
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Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review.

The Lancet. Digital health Nov 23, 2021
Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key u...
Machine Learning Drug-Related Side Effects and Adverse Reactions Humans Artificial Intelligence
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A unified drug-target interaction prediction framework based on knowledge graph and recommendation system.

Nature communications Nov 22, 2021
Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfe...
Drug Interactions Drug-Related Side Effects and Adverse Reactions Pattern Recognition, Automated Drug Repositioning Pharmaceutical Preparations Knowledge Models, Theoretical Drug Development Machine Learning
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A Deep Learning-Based Text Classification of Adverse Nursing Events.

Journal of healthcare engineering Nov 18, 2021
Adverse nursing events occur suddenly, unpredictably, or unexpectedly during course of clinical diagnosis and treatment processes in the hospitals. These events adversely affect the patient's diagnosis and treatment results and even increase the pati...
Humans Deep Learning Patient Safety Drug-Related Side Effects and Adverse Reactions Hospitals Delivery of Health Care
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A sui generis QA approach using RoBERTa for adverse drug event identification.

BMC bioinformatics Oct 21, 2021
BACKGROUND: 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 aroun...
Drug-Related Side Effects and Adverse Reactions Humans Neural Networks, Computer
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Automation of penicillin adverse drug reaction categorisation and risk stratification with machine learning natural language processing.

International journal of medical informatics Oct 5, 2021
BACKGROUND: The penicillin adverse drug reaction (ADR) label is common in electronic health records (EHRs). However, there is significant misclassification between allergy and intolerance within the EHR and most patients can be delabelled after an im...
Automation Penicillins Algorithms Electronic Health Records Natural Language Processing Risk Assessment Drug-Related Side Effects and Adverse Reactions Humans Machine Learning
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AttentionDDI: Siamese attention-based deep learning method for drug-drug interaction predictions.

BMC bioinformatics Aug 21, 2021
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 drug pair...
Humans Neural Networks, Computer Deep Learning Drug-Related Side Effects and Adverse Reactions Pharmaceutical Preparations Drug Interactions
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A case of fatal multidrug intoxication involving flualprazolam: distribution in body fluids and solid tissues.

Forensic toxicology Aug 11, 2021
PURPOSE: Designer benzodiazepines (DBZDs) increasingly emerged on the novel psychoactive substance (NPS) market in the last few years. They are usually sold as readily available alternatives to prescription benzodiazepines (BZDs) or added to counterf...
Drug-Related Side Effects and Adverse Reactions Benzodiazepines Humans Alprazolam Body Fluids
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Machine Learning Approach for Active Vaccine Safety Monitoring.

Journal of Korean medical science Aug 9, 2021
BACKGROUND: Vaccine safety surveillance is important because it is related to vaccine hesitancy, which affects vaccination rate. To increase confidence in vaccination, the active monitoring of vaccine adverse events is important. For effective active...
Drug-Related Side Effects and Adverse Reactions Adverse Drug Reaction Reporting Systems Vaccination Anaphylaxis Humans Databases, Factual Product Surveillance, Postmarketing Vaccines Agranulocytosis Republic of Korea Machine Learning
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