Corporate Social Responsibility and Environmental Management, EarlyView.ABSTRACT This study examines the relationship between artificial intelligence and both environmental and social sustainability practices in small and medium‐sized enterprises, with a specific focus on the moderating effects of implementation barriers relating to sustainability, digitalization, and innovation.
Gülçinay Mumcu, Steven A. Brieger
wiley +1 more source
Post-licensure safety surveillance of 9-valent human papillomavirus vaccine using the vaccine adverse event reporting system, 2014-2024. [PDF]
Front Public HealthChen JH, Chen M, Wu ZY, Luo QM, Tu YY.
europepmc +1 more source
AIM2 framework for smart marketing innovation using AI driven consumer analytics with SOR neural networks and XGBoost in Saudi retail. [PDF]
Sci RepAlarfaj FK +3 more
europepmc +1 more source
Vitamin D Status and Selected Metabolic Parameters in Salt Mine Workers: A Cross-Sectional Study. [PDF]
NutrientsPietrzak M, Sobczak K, Domaszewska K.
europepmc +1 more source
Integrated Evidence from VigiBase and Clinical Trials: A Comprehensive Pharmacovigilance Analysis of Seven Glucagon-Like Peptide 1 Receptor Agonists (GLP-1 RAs). [PDF]
Diabetes TherLi J, Liang J, Zhang W, He J, Ye X.
europepmc +1 more source
An Integrated Text Mining Approach for Discovering Pharmacological Effects, Drug Combinations, and Repurposing Opportunities of ACE Inhibitors. [PDF]
Int J Mol SciBiziukova NY +4 more
europepmc +1 more source
Risk Assessment of Lead and Cadmium Exposure Through Raw Milk Consumption from Small-Scale Dairy Systems in the Central Peruvian Andes. [PDF]
ToxicsChirinos-Peinado D +4 more
europepmc +1 more source
Granger causality-based cluster sequence mining for spatio-temporal causal relation mining
International Journal of Data Science and Analytics, 2023 AbstractWe proposed a method to extract causal relations of spatial clusters from multi-dimensional event sequence data, also known as a spatio-temporal point process. The proposed Granger cluster sequence mining algorithm identifies the pairs of spatial data clusters that have causality over time with each other.
Ken-Ichi Fukui +2 more
exaly +2 more sources
Scalable Techniques for Mining Causal Structures [PDF]
Data Mining and Knowledge Discovery, 2000 Mining for association rules in market basket data has proved a fruitful area of research. Measures such as conditional probability (confidence) and correlation have been used to infer rules of the form “the existence of item A implies the existence of item B.” However, such rules indicate only a statistical relationship between A and B.
Craig Silverstein +3 more
openaire +1 more source
Related searches:
Mining Causal Association Rules
2013 IEEE 13th International Conference on Data Mining Workshops, 2013Discovering causal relationships is the ultimate goal of many scientific explorations. Causal relationships can be identified with controlled experiments, but such experiments are often very expensive and sometimes impossible to conduct. On the other hand, the collection of observational data has increased dramatically in recent decades.
Jiuyong Li +5 more
openaire +1 more source