Open Heart

AI-enhanced electrocardiography as a digital biomarker platform in cardiovascular medicine: clinical applications, validation gaps and future implementation pathways

Artificial intelligence applied to the ECG is expanding the clinical role of this widely available diagnostic tool beyond ...

Deep learning reveals nanoparticle shape from routine tracking analysis without new hardware

Researchers at the University of Tokyo and the Innovation Center of NanoMedicine (iCONM) have developed an artificial ...
Communications of the ACM

Can We Understand How Large Language Models Reason?

Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how ...

Researchers develop AI tool that finds the equations behind complex systems

Clarkson University researchers have developed an artificial intelligence tool that can uncover the mathematical equations ...

WiMi Develops Quantum Convolutional Neural Network Model for Classical Data Classification

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WIMI" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, has completed systematic benchmark testing on fully ...
AlphaGalileo

Breakthrough in Efficient GNN Training Architecture: Research Team Proposes Hardware-Algorithm Co-Optimization Solution

A Chinese research team has achieved a breakthrough in improving the training efficiency of Graph Neural Networks (GNNs). They introduced an ...
The New York Times

Europe Accuses TikTok of ‘Addictive Design’ and Pushes for Change

European Union regulators said the app’s infinite scroll and personalized algorithm led to “compulsive” behavior, especially among children. By Adam Satariano Reporting from London TikTok’s endless ...
Frontiers

Bidirectional cross-day alignment of neural spikes and behavior using a hybrid SNN-ANN algorithm

Recent advances in deep learning have enabled effective interpretation of neural activity patterns from electroencephalogram signals; however, challenges persist in invasive brain signals for ...
IEEE

Multiscale Convolutional Neural Network With Self-Attention Mechanism and Soft Thresholding for Industrial Process Fault Diagnosis

Abstract: This article proposes a multiscale convolutional neural network (MSCNN)-based fault diagnosis method (AM-MAST) using a self-attention mechanism and soft thresholding. It aims to improve the ...