… study of the association between antipsychotic drugs and venous thromboembolism based on Food and Drug Administration Adverse Event Reporting System data
Y Yan, L Wang, Y Yuan, J Xu, Y Chen… - Expert Opinion on Drug …, 2024 - Taylor & Francis
… by antipsychotic drugs is one of the adverse drug reactions. … using data mining methods to
detect signals of drug-related … However, platelet aggregation mainly leads to arterial clots, not …
detect signals of drug-related … However, platelet aggregation mainly leads to arterial clots, not …
Overview of the first natural language processing challenge for extracting medication, indication, and adverse drug events from electronic health record notes (MADE …
… pharmacovigilance, “the science and activities relating to the detection, assessment, …
Perform an ensemble-based system aggregation that shows that the top systems are …
Perform an ensemble-based system aggregation that shows that the top systems are …
An overview of machine learning and big data for drug toxicity evaluation
AH Vo, TR Van Vleet, RR Gupta… - Chemical research in …, 2019 - ACS Publications
… animal to human data for 142 approved drugs and reported … (10) However, the concordance
for adverse drug reactions in … compounds, detect outliers, and reduce or simplify data to …
for adverse drug reactions in … compounds, detect outliers, and reduce or simplify data to …
Machine learning and data mining in manufacturing
A Dogan, D Birant - Expert Systems with Applications, 2021 - Elsevier
Manufacturing organizations need to use different kinds of techniques and tools in order to
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining (DM) …
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining (DM) …
Toward better drug discovery with knowledge graph
… that implement drug repurposing and adverse drug reaction prediction for drug discovery.
As … are jointly propagated and updated in a recursive aggregation process. Feeney et al. [51] …
As … are jointly propagated and updated in a recursive aggregation process. Feeney et al. [51] …
Spatiotemporal data mining: a survey on challenges and open problems
… detection, association and pattern mining, outlier detection, … , spatiotemporal discretisation
(or aggregation) is applied. The … point but requires the aggregation of the crimes occurred in …
(or aggregation) is applied. The … point but requires the aggregation of the crimes occurred in …
Open Targets Platform: supporting systematic drug–target identification and prioritisation
… adverse drug reactions from the FDA Adverse Event Reporting System (FAERS) for approved
drugs, … provides more in-depth aggregation and analysis of data. Users can also rearrange …
drugs, … provides more in-depth aggregation and analysis of data. Users can also rearrange …
An integrated cluster detection, optimization, and interpretation approach for financial data
… the most important ones and took negative effects, while the 5th feature … aggregation degree
of data points inside the cluster. Then, we designed an adaptive algorithm AdaEllip to detect …
of data points inside the cluster. Then, we designed an adaptive algorithm AdaEllip to detect …
Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine
… learning platforms for clinical data extraction, aggregation, management and analysis can
… academic solutions in paving the way for a new data-centric era of discovery in healthcare. …
… academic solutions in paving the way for a new data-centric era of discovery in healthcare. …
A BIM-data mining integrated digital twin framework for advanced project management
… discovery of the process model by proper process mining … the distance of events to determine
behavior aggregation and abstraction… negative effects from potential bottlenecks if possible. …
behavior aggregation and abstraction… negative effects from potential bottlenecks if possible. …