Tag: deep learning

Researchers in Wuhan developed a two-stage deep learning system that detects and classifies postoperative coughs from audio recordings of lung ...

Researchers have unveiled MassNet, a corpus of 1.5 billion mass spectra across 35 species, and a new transformer model that ...

Researchers have developed X-URL, a character-level deep learning framework that classifies malicious URLs into four threat categories with over 98 ...

A new hybrid framework called HDOCK-Multimer combines protein-protein docking with combinatorial assembly to predict the structures of large protein complexes ...

A new deep learning radiomics model built on preoperative multiparametric MRI achieved AUCs up to 0.95 in predicting three-year breast ...

Korean researchers have built a hybrid Vision Transformer and CNN generative model that enhances ultrasound image quality with state-of-the-art fidelity ...

A new scoping review maps how artificial intelligence is being tested across emergency care and disaster response, and finds that ...

Researchers combined reconstructed phase space representations, a 3D convolutional neural network, and gray wolf optimizer tuning to achieve state-of-the-art cross-corpus ...

A new survey in the Journal of Big Data uses machine learning, deep learning, and advanced analytics to evaluate the ...

An Indian research team has developed GraphX, an explainable graph transformer framework that classifies nail diseases with 94.97 percent accuracy ...

Two interpretable neural network frameworks, xNNDriver and xAEDriver, mine genome-wide cancer dependency data to prioritize driver genes, pathways, and therapeutic ...

A new deep learning framework can detect six types of cyber-attacks on EEG signals and reconstruct the corrupted brain data ...

Researchers have reimagined pixels as three-dimensional cuboids whose sizes are set by RGB values, using the empty space between them ...

A two-stage Vision Transformer–U-Net pipeline restores reliable detection of rare voids in concrete X-ray CT images where single-stage deep learning ...

A large retrospective benchmark across six countries and more than 70 infectious diseases finds that zero-shot time series foundation models ...

A reproducibility study of 18 influential papers finds that data leakage, silently modified datasets, and underspecified baselines have inflated claims ...

A new safety audit shows that machine unlearning in medical AI can silently degrade performance on rare diagnoses, and proposes ...

A new multi-dimensional evaluation framework shows that the most accurate intrusion detection model is often not the best choice for ...

A new convolutional architecture called MRTFNet combines multi-resolution temporal embeddings with frequency-domain modeling to outperform Transformer-based models on most long-term ...

A deep learning model trained exclusively on adult duodenal biopsy images has achieved pathologist-level accuracy in diagnosing coeliac disease in ...