AI Tool Uncovers Hundreds of Hidden Cosmic Oddities in Hubble Data

A team of astronomers based at the European Space Agency demonstrated how artificial intelligence technology will alter existing methods of locating rare astronomical phenomena within our galaxy, the ...
AZoSensors on MSN

Machine-learning technique shown to reduce sensor drift in electronic noses

Research reveals that knowledge distillation significantly compensates for sensor drift in electronic noses, improving ...
Becker's Hospital Review

UCLA Health develops AI to detect undiagnosed Alzheimer’s cases

Researchers at Los Angeles-based UCLA Health have developed an AI model that uses EHRs to identify patients with undiagnosed Alzheimer’s disease. The model was trained on records from more than 97,000 ...
Frontiers

Mapping soil salinity using machine learning and remote sensing data in semi-arid croplands

Soil salinity significantly constrains agricultural productivity and land sustainability, particularly in irrigated areas. While, remote sensing offers large-scale monitoring capacity, but its ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...
GitHub

arya-gaj/listening-beyond-the-labels-v1

Alzheimer's Disease (AD), a progressive neurodegenerative condition of cognitive decline, presents formidable challenges to patients, caregivers, and healthcare systems. Early identification is ...
Scientific Research Publishing

Sen, P.C., Hajra, M. and Ghosh, M. (2019) Supervised Classification Algorithms in Machine Learning: A Survey and Review. In: Mandal, J.K. and Bhattacharya, D., Eds., Emerging ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
BizTech

What Are the Benefits of Unsupervised Machine Learning and Clustering?

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...
IEEE

An Analysis of Semi-Supervised Machine Learning in Electrical Machines

Abstract: This research outlines the significance of semi-supervised machine learning (SSML) in dealing with the intricate characteristics of electrical machines. SSML provides a key benefit in ...