Blockchain Meets Machine Learning to Catch Money Launderers With 96% Accuracy
Researchers have combined blockchain-based customer authentication with an ensemble of three machine learning classifiers to detect money laundering with 96.68 ...
Researchers have combined blockchain-based customer authentication with an ensemble of three machine learning classifiers to detect money laundering with 96.68 ...
A multicenter study shows that an explainable machine learning model combining cardiac CT angiography features with clinical data can predict ...
Researchers have developed an RBF neural network framework that combines physics-based trend monitoring with deep learning to detect, isolate, and ...
The latest volume of SLAS Discovery showcases how artificial intelligence, deep learning and data-mining strategies are accelerating drug discovery across ...
A new Perspective argues that electrically and magnetically driven active colloids should be understood as distributed micromachines whose power, sensing, ...
A new graph-structured Transformer model trained with self-supervised learning and community-consensus pseudo-labeling achieves record F1-scores for detecting cryptocurrency money laundering ...
A new leakage-audited benchmark shows that random data splitting inflates toxicity model performance by up to 0.079 AUROC points while ...
A real-world clinical validation of a commercial AI system for prostate MRI found high sensitivity for clinically significant cancer but ...
Researchers in India have built a reinforcement learning trading agent that combines generative language model sentiment analysis with proximal policy ...
An integrative bioinformatics and RT-qPCR study nominates ALDH3B1 and ALOX15B as preliminary mitochondrial metabolism-related candidate genes in major depressive disorder.
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© 2025 Scienmag - Science Magazine