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Decoding high energy physics with AI and machine learning
In the world of particle physics, where scientists unravel the mysteries of the universe, artificial intelligence (AI) and ...
Tech Xplore8h
Explainable AI: New framework increases transparency in decision-making systems
A new explainable AI technique transparently classifies images without compromising accuracy. The method, developed at the ...
The American Journal of Managed Care1d
AI-Based Tool for Classifying Acute Leukemia Subtypes Shows Promise in Global Study: Merlin Engelke, MS
An artificial intelligence (AI)-driven machine learning model was refined and validated internationally to accurately classify acute leukemia subtypes from routine laboratory data, according to Merlin ...
Tech Xplore1d
Innovative detection method makes AI smarter by cleaning up bad data before it learns
In the world of machine learning and artificial intelligence, clean data is everything. Even a small number of mislabeled ...
Unprecedented dataset of molecular simulations to train AI models released
A collaborative effort between Meta, Lawrence Berkeley National Laboratory and Los Alamos National Laboratory leverages Los ...
Scientific Research Publishing8d
A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites ()
Budoen, A.T., Zhang, M.W. and Edwards Jr., L.Z. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, ...
eLife14d
Deep Learning Reveals Endogenous Sterols as Allosteric Modulators of the GPCR-Gα Interface
Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...
IEEE16d
Few-Shot Automatic Modulation Classification via Semi-Supervised Metric Learning and Lightweight Conv-Transformer Model
Abstract: Deep learning (DL ... SMCTNet reduces the difficulty of model optimization by utilizing a parameter-free metric that directly calculates the similarity between output characteristics for ...
Frontiers29d
Brain tumor classification from MRI scans: a framework of hybrid deep learning model with Bayesian optimization and quantum theory-based marine predator algorithm
Brain tumor classification is one ... area of research is the deep learning-based categorization of brain tumors using brain magnetic resonance imaging (MRI). This paper proposes an automated deep ...
IEEE29d
ST-LLM+: Graph Enhanced Spatio-Temporal Large Language Models for Traffic Prediction
large language models (LLMs) progress mainly through parameter expansion and extensive pre-training while maintaining their fundamental structures. In this paper, we propose ST-LLM+, the graph ...