AI model predicts neural network degeneration patterns in ALS progression

New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI ...
IEEE

Mitigating Poisoning Attacks in Federated Learning Through Deep One-Class Classification

Abstract: Federated learning (FL) enables clients to learn a machine learning model collaboratively without sharing their private local data to the server. However, due to its distributed structure, ...

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
MobiHealthNews

Finding the optimal epilepsy drug using AI in Korea

Seoul National University Hospital researchers have developed an AI model that predicts the response to an anticonvulsant ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
TDAN.com

Using Artificial Intelligence and Machine learning to Improve Data Quality in Cloud Native Data Pipelines

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
Frontiers

A clinical prediction model for schizophrenia based on machine learning algorithms

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...
IEEE

Pattern-Based Feature Extraction for Improved Deep Learning in Financial Time Series Classification

Abstract: In this paper, the authors introduce a novel feature extraction method based on pattern detection in financial data to enhance the performance of deep learning models for financial time ...