RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
BMJ Open

Implementation determinants of a planned machine learning-enabled surgical scheduling system in a high-volume orthopaedic centre in Canada: qualitative findin…

Objectives Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room ...
PC Tech Magazine

Best machine learning development companies for time series forecasting (2026)

The seven companies listed here cover the realistic range of what a buyer will encounter in 2026: embedded ML teams that own ...

Reinforcement learning improves execution quality in financial markets

Alex Chen's adaptive execution framework, using reinforcement learning, cuts trading costs and improves market visibility.
AZoM

Berkeley Lab Uses Advanced Machine Learning to Optimize Chiral Perovskites

Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the ...
European Medical Journal

Machine Learning Links Gut Microbiome to Improved DVT Detection

AI model suggests deep vein thrombosis may be identified more accurately using gut microbiome profiles. Read more.

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 ...
IEEE

Enhancing Phishing Detection: A Machine Learning Approach With Feature Selection and Deep Learning Models

Abstract: With the rise in cybercrime, phishing remains a significant concern as it targets individuals with fake websites, causing victims to disclose their private information. The effective ...
IEEE

Hybrid Deep Machine Learning Feature Selection for High-Dimensional Cybersecurity Data

Abstract: The rapid increase in cyber threats has heightened the demand for Intrusion Detection Systems (IDS) that are both accurate and efficient. While deep learning models outperform traditional ...
Beebom

What is the Difference Between Deep Learning and Machine Learning

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...