Trains on MSN

Startup's drones use high-tech to find coupler problems in yards

HOUSTON — Tech startup Unspace was founded in 2020. Since 2022, it has been advancing machine learning in the field of machine vision to improve rail safety and operational efficiency, a journey that ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

An Overview and Classification of Machine Learning Approaches for Radar Signal Deinterleaving

Abstract: Electronic Warfare (EW) receivers are passive systems that are designed to detect and identify active radar emitters in the environment. The radar pulses emitted by multiple sources are ...
Phys.org

Machine learning helps solve a central problem of quantum chemistry

Within the STRUCTURES Cluster of Excellence, two research teams at the Interdisciplinary Center for Scientific Computing (IWR) have refined a computing process, long held to be unreliable, such that ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
Scientific Research Publishing

Altalhan, M., Algarni, A. and Turki-Hadj Alouane, M. (2025) Imbalanced Data Problem in Machine Learning: A Review. IEEE Access, 13, 13686-13699.

ABSTRACT: Mood disorders—particularly bipolar spectrum conditions—pose enduring diagnostic and therapeutic challenges due to their episodic nature, heterogeneous presentations, and reliance on ...
National Review

Democracy’s Machine Learning Problem

‘America Bad’ Isn’t the Right Theme for America’s 250th The Pro-Trans Movement Has No Credibility Left. Time to Say ‘Game Over’ Toy Story 5 vs. Drunken Noodles 1776? The American Revolution Really ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

In many countries, patients with headache disorders such as migraine remain under-recognized and under-diagnosed. Patients affected by these disorders are often unaware of the seriousness of their ...
GitHub

basic-binary-classification-problem

This repository contains two basic prediction models: Credit Card Fraud Detection and Titanic Survival Prediction. Both models demonstrate the use of machine learning for binary classification tasks.
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...
Scientific Research Publishing

Research on Fault Detection and Classification of Industrial Equipment Based on Machine Learning ()

In the context of the rapid development of intelligent manufacturing, the stable operation of mechanical equipment is crucial for maintaining industrial production continuity and achieving economic ...