Humans and artificial neural networks exhibit some similar patterns during learning

Past psychology and behavioral science studies have identified various ways in which people's acquisition of new knowledge ...
Tech Xplore

BrainBody-LLM algorithm helps robots mimic human-like planning and movement

Large language models (LLMs), such as the model underpinning the functioning of OpenAI's platform ChatGPT, are now widely ...
eLife

TSvelo: Comprehensive RNA velocity by modeling the cascade of gene regulation, transcription and splicing

This study presents a valuable tool named TSvelo, a computational framework for RNA velocity inference that models transcriptional regulation and gene-specific splicing. The evidence supporting the ...
AlphaGalileo

Smart tea agriculture: machine learning opens new pathways for quality and sustainability

A research team has mapped how machine learning is transforming the global tea industry, revealing that data-driven ...
EurekAlert!

An interpretable machine learning model for predicting 5‐year survival in breast cancer based on integration of proteomics and clinical data

Breast cancer is a highly heterogeneous malignancy among women worldwide. Traditional prognostic models relying solely on ...
Business Wire

HeartBeam’s Deep Learning Algorithms Demonstrate High Rates of Accuracy for Detecting Arrhythmias

New study presented at HRX Live 2025 demonstrates continued advancement of company’s AI program HeartBeam's AI algorithm performed equally well on HeartBeam 3D ECG system and standard 12L ECGs in ...
Finbold | Finance in Bold

Machine learning algorithm suggests NVIDIA could hit this price in September

Nvidia (NASDAQ: NVDA) reports earnings today with sky-high projections surpassing $46 billion in revenue and $1.01 earnings per share (EPS). The results will also double as a litmus test for Trump’s ...
EurekAlert!

Neuromorphic devices and machine learning combine to make brain-like devices possible

As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...
Frontiers

SHAP combined with machine learning to predict mortality risk in maintenance hemodialysis patients: a retrospective study

Background: Patients undergoing maintenance hemodialysis face a high mortality rate, yet effective tools for predicting mortality risk in this population are lacking. This study aims to develop an ...
IEEE

Application of K-Nearest Neighbor Machine Learning Algorithm in High Voltage Circuit Breaker Monitoring System by Analyzing Spring Mechanism Motor Current

Abstract: Machine learning has been applied across various scientific fields and switching apparatus monitoring is no exception. Monitoring system is a crucial component of switching apparatus ...